From 32296385baa94a3d7a03ca42f7c603067fab327c Mon Sep 17 00:00:00 2001
From: Godot115 <godot.is.me@gmail.com>
Date: Mon, 15 Apr 2024 05:38:51 +0800
Subject: [PATCH 1/3] fix bugs: Update examples and docs for breaking changes
 in v3.0.0

- Change ClassName to NewClassName (mostly are BaseXXX to DevXXX) in docs/source/pages/general/advances/import_all_models.rst and examples/run_all_parameters.py
- Rename fit_func to obj_func in examples/applications/pytorch/linear_regression.py. Bug in issue 147 is fixed https://github.com/thieu1995/mealpy/issues/147.
---
 .../general/advances/import_all_models.rst    | 1738 ++++++++---------
 .../applications/pytorch/linear_regression.py |    2 +-
 examples/run_all_parameters.py                |   64 +-
 3 files changed, 902 insertions(+), 902 deletions(-)

diff --git a/docs/source/pages/general/advances/import_all_models.rst b/docs/source/pages/general/advances/import_all_models.rst
index f189ebc2..8e61fd85 100644
--- a/docs/source/pages/general/advances/import_all_models.rst
+++ b/docs/source/pages/general/advances/import_all_models.rst
@@ -3,894 +3,894 @@ Import All Models
 
 .. code-block:: python
 
-	from mealpy import BBO, PSO, GA, ALO, AO, ARO, AVOA, BA, BBOA, BMO, EOA, IWO
-	from mealpy import SBO, SMA, SOA, SOS, TPO, TSA, VCS, WHO, AOA, CEM, CGO, CircleSA, GBO, HC, INFO, PSS, RUN, SCA
-	from mealpy import SHIO, TS, HS, AEO, GCO, WCA, CRO, DE, EP, ES, FPA, MA, SHADE, BRO, BSO, CA, CHIO, FBIO, GSKA, HBO
-	from mealpy import HCO, ICA, LCO, WarSO, TOA, TLO, SSDO, SPBO, SARO, QSA, ArchOA, ASO, CDO, EFO, EO, EVO, FLA
-	from mealpy import HGSO, MVO, NRO, RIME, SA, WDO, TWO, ABC, ACOR, AGTO, BeesA, BES, BFO, ZOA, WOA, WaOA, TSO
-	from mealpy import TDO, STO, SSpiderO, SSpiderA, SSO, SSA, SRSR, SLO, SHO, SFO, ServalOA, SeaHO, SCSO, POA
-	from mealpy import PFA, OOA, NGO, NMRA, MSA, MRFO, MPA, MGO, MFO, JA, HHO, HGS, HBA, GWO, GTO, GOA
-	from mealpy import GJO, FOX, FOA, FFO, FFA, FA, ESOA, EHO, DO, DMOA, CSO, CSA, CoatiOA, COA, BSA
-	from mealpy import StringVar, FloatVar, BoolVar, PermutationVar, MixedSetVar, IntegerVar, BinaryVar
-	from mealpy import Tuner, Multitask, Problem, Optimizer, Termination, ParameterGrid
-	from mealpy import get_all_optimizers, get_optimizer_by_name
-	import numpy as np
+    from mealpy import BBO, PSO, GA, ALO, AO, ARO, AVOA, BA, BBOA, BMO, EOA, IWO
+    from mealpy import SBO, SMA, SOA, SOS, TPO, TSA, VCS, WHO, AOA, CEM, CGO, CircleSA, GBO, HC, INFO, PSS, RUN, SCA
+    from mealpy import SHIO, TS, HS, AEO, GCO, WCA, CRO, DE, EP, ES, FPA, MA, SHADE, BRO, BSO, CA, CHIO, FBIO, GSKA, HBO
+    from mealpy import HCO, ICA, LCO, WarSO, TOA, TLO, SSDO, SPBO, SARO, QSA, ArchOA, ASO, CDO, EFO, EO, EVO, FLA
+    from mealpy import HGSO, MVO, NRO, RIME, SA, WDO, TWO, ABC, ACOR, AGTO, BeesA, BES, BFO, ZOA, WOA, WaOA, TSO
+    from mealpy import TDO, STO, SSpiderO, SSpiderA, SSO, SSA, SRSR, SLO, SHO, SFO, ServalOA, SeaHO, SCSO, POA
+    from mealpy import PFA, OOA, NGO, NMRA, MSA, MRFO, MPA, MGO, MFO, JA, HHO, HGS, HBA, GWO, GTO, GOA
+    from mealpy import GJO, FOX, FOA, FFO, FFA, FA, ESOA, EHO, DO, DMOA, CSO, CSA, CoatiOA, COA, BSA
+    from mealpy import StringVar, FloatVar, BoolVar, PermutationVar, MixedSetVar, IntegerVar, BinaryVar
+    from mealpy import Tuner, Multitask, Problem, Optimizer, Termination, ParameterGrid
+    from mealpy import get_all_optimizers, get_optimizer_by_name
+    import numpy as np
 
-	def objective_function(solution):
-	    return np.sum(solution ** 2)
+    def objective_function(solution):
+        return np.sum(solution ** 2)
 
-	problem = {
-	    "obj_func": objective_function,
-	    "bounds": FloatVar(lb=[-3] * 20, ub=[5] * 20),
-	    "name": "Squared Problem",
-	    "log_to": "file",
-	    "log_file": "results.log"
-	}
+    problem = {
+        "obj_func": objective_function,
+        "bounds": FloatVar(lb=[-3] * 20, ub=[5] * 20),
+        "name": "Squared Problem",
+        "log_to": "file",
+        "log_file": "results.log"
+    }
 
-	paras_bbo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "p_m": 0.01,
-	    "elites": 2,
-	}
-	paras_eoa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "p_c": 0.9,
-	    "p_m": 0.01,
-	    "n_best": 2,
-	    "alpha": 0.98,
-	    "beta": 0.9,
-	    "gamma": 0.9,
-	}
-	paras_iwo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "seed_min": 3,
-	    "seed_max": 9,
-	    "exponent": 3,
-	    "sigma_start": 0.6,
-	    "sigma_end": 0.01,
-	}
-	paras_sbo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "alpha": 0.9,
-	    "p_m": 0.05,
-	    "psw": 0.02,
-	}
-	paras_sma = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "p_t": 0.03,
-	}
-	paras_vcs = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "lamda": 0.5,
-	    "sigma": 0.3,
-	}
-	paras_who = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "n_explore_step": 3,
-	    "n_exploit_step": 3,
-	    "eta": 0.15,
-	    "p_hi": 0.9,
-	    "local_alpha": 0.9,
-	    "local_beta": 0.3,
-	    "global_alpha": 0.2,
-	    "global_beta": 0.8,
-	    "delta_w": 2.0,
-	    "delta_c": 2.0,
-	}
-	paras_cro = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "po": 0.4,
-	    "Fb": 0.9,
-	    "Fa": 0.1,
-	    "Fd": 0.1,
-	    "Pd": 0.5,
-	    "GCR": 0.1,
-	    "gamma_min": 0.02,
-	    "gamma_max": 0.2,
-	    "n_trials": 5,
-	}
-	paras_ocro = dict(paras_cro)
-	paras_ocro["restart_count"] = 5
+    paras_bbo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "p_m": 0.01,
+        "elites": 2,
+    }
+    paras_eoa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "p_c": 0.9,
+        "p_m": 0.01,
+        "n_best": 2,
+        "alpha": 0.98,
+        "beta": 0.9,
+        "gamma": 0.9,
+    }
+    paras_iwo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "seed_min": 3,
+        "seed_max": 9,
+        "exponent": 3,
+        "sigma_start": 0.6,
+        "sigma_end": 0.01,
+    }
+    paras_sbo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "alpha": 0.9,
+        "p_m": 0.05,
+        "psw": 0.02,
+    }
+    paras_sma = {
+        "epoch": 20,
+        "pop_size": 50,
+        "p_t": 0.03,
+    }
+    paras_vcs = {
+        "epoch": 20,
+        "pop_size": 50,
+        "lamda": 0.5,
+        "sigma": 0.3,
+    }
+    paras_who = {
+        "epoch": 20,
+        "pop_size": 50,
+        "n_explore_step": 3,
+        "n_exploit_step": 3,
+        "eta": 0.15,
+        "p_hi": 0.9,
+        "local_alpha": 0.9,
+        "local_beta": 0.3,
+        "global_alpha": 0.2,
+        "global_beta": 0.8,
+        "delta_w": 2.0,
+        "delta_c": 2.0,
+    }
+    paras_cro = {
+        "epoch": 20,
+        "pop_size": 50,
+        "po": 0.4,
+        "Fb": 0.9,
+        "Fa": 0.1,
+        "Fd": 0.1,
+        "Pd": 0.5,
+        "GCR": 0.1,
+        "gamma_min": 0.02,
+        "gamma_max": 0.2,
+        "n_trials": 5,
+    }
+    paras_ocro = dict(paras_cro)
+    paras_ocro["restart_count"] = 5
 
-	paras_de = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "wf": 0.7,
-	    "cr": 0.9,
-	    "strategy": 0,
-	}
-	paras_jade = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "miu_f": 0.5,
-	    "miu_cr": 0.5,
-	    "pt": 0.1,
-	    "ap": 0.1,
-	}
-	paras_sade = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_shade = paras_lshade = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "miu_f": 0.5,
-	    "miu_cr": 0.5,
-	}
-	paras_sap_de = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "branch": "ABS"
-	}
-	paras_ep = paras_levy_ep = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "bout_size": 0.05
-	}
-	paras_es = paras_levy_es = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "lamda": 0.75
-	}
-	paras_fpa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "p_s": 0.8,
-	    "levy_multiplier": 0.2
-	}
-	paras_ga = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pc": 0.9,
-	    "pm": 0.05,
-	}
-	paras_single_ga = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pc": 0.9,
-	    "pm": 0.8,
-	    "selection": "roulette",
-	    "crossover": "uniform",
-	    "mutation": "swap",
-	}
-	paras_multi_ga = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pc": 0.9,
-	    "pm": 0.05,
-	    "selection": "roulette",
-	    "crossover": "uniform",
-	    "mutation": "swap",
-	}
-	paras_ma = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pc": 0.85,
-	    "pm": 0.15,
-	    "p_local": 0.5,
-	    "max_local_gens": 10,
-	    "bits_per_param": 4,
-	}
+    paras_de = {
+        "epoch": 20,
+        "pop_size": 50,
+        "wf": 0.7,
+        "cr": 0.9,
+        "strategy": 0,
+    }
+    paras_jade = {
+        "epoch": 20,
+        "pop_size": 50,
+        "miu_f": 0.5,
+        "miu_cr": 0.5,
+        "pt": 0.1,
+        "ap": 0.1,
+    }
+    paras_sade = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_shade = paras_lshade = {
+        "epoch": 20,
+        "pop_size": 50,
+        "miu_f": 0.5,
+        "miu_cr": 0.5,
+    }
+    paras_sap_de = {
+        "epoch": 20,
+        "pop_size": 50,
+        "branch": "ABS"
+    }
+    paras_ep = paras_levy_ep = {
+        "epoch": 20,
+        "pop_size": 50,
+        "bout_size": 0.05
+    }
+    paras_es = paras_levy_es = {
+        "epoch": 20,
+        "pop_size": 50,
+        "lamda": 0.75
+    }
+    paras_fpa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "p_s": 0.8,
+        "levy_multiplier": 0.2
+    }
+    paras_ga = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pc": 0.9,
+        "pm": 0.05,
+    }
+    paras_single_ga = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pc": 0.9,
+        "pm": 0.8,
+        "selection": "roulette",
+        "crossover": "uniform",
+        "mutation": "swap",
+    }
+    paras_multi_ga = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pc": 0.9,
+        "pm": 0.05,
+        "selection": "roulette",
+        "crossover": "uniform",
+        "mutation": "swap",
+    }
+    paras_ma = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pc": 0.85,
+        "pm": 0.15,
+        "p_local": 0.5,
+        "max_local_gens": 10,
+        "bits_per_param": 4,
+    }
 
-	paras_bro = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "threshold": 3,
-	}
-	paras_improved_bso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "m_clusters": 5,
-	    "p1": 0.2,
-	    "p2": 0.8,
-	    "p3": 0.4,
-	    "p4": 0.5,
-	}
-	paras_bso = dict(paras_improved_bso)
-	paras_bso["slope"] = 20
-	paras_ca = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "accepted_rate": 0.15,
-	}
-	paras_chio = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "brr": 0.15,
-	    "max_age": 3
-	}
-	paras_fbio = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_base_gska = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pb": 0.1,
-	    "kr": 0.9,
-	}
-	paras_gska = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pb": 0.1,
-	    "kf": 0.5,
-	    "kr": 0.9,
-	    "kg": 5,
-	}
-	paras_ica = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "empire_count": 5,
-	    "assimilation_coeff": 1.5,
-	    "revolution_prob": 0.05,
-	    "revolution_rate": 0.1,
-	    "revolution_step_size": 0.1,
-	    "zeta": 0.1,
-	}
-	paras_lco = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "r1": 2.35,
-	}
-	paras_improved_lco = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_qsa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_saro = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "se": 0.5,
-	    "mu": 15
-	}
-	paras_ssdo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_tlo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_improved_tlo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "n_teachers": 5,
-	}
+    paras_bro = {
+        "epoch": 20,
+        "pop_size": 50,
+        "threshold": 3,
+    }
+    paras_improved_bso = {
+        "epoch": 20,
+        "pop_size": 50,
+        "m_clusters": 5,
+        "p1": 0.2,
+        "p2": 0.8,
+        "p3": 0.4,
+        "p4": 0.5,
+    }
+    paras_bso = dict(paras_improved_bso)
+    paras_bso["slope"] = 20
+    paras_ca = {
+        "epoch": 20,
+        "pop_size": 50,
+        "accepted_rate": 0.15,
+    }
+    paras_chio = {
+        "epoch": 20,
+        "pop_size": 50,
+        "brr": 0.15,
+        "max_age": 3
+    }
+    paras_fbio = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_base_gska = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pb": 0.1,
+        "kr": 0.9,
+    }
+    paras_gska = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pb": 0.1,
+        "kf": 0.5,
+        "kr": 0.9,
+        "kg": 5,
+    }
+    paras_ica = {
+        "epoch": 20,
+        "pop_size": 50,
+        "empire_count": 5,
+        "assimilation_coeff": 1.5,
+        "revolution_prob": 0.05,
+        "revolution_rate": 0.1,
+        "revolution_step_size": 0.1,
+        "zeta": 0.1,
+    }
+    paras_lco = {
+        "epoch": 20,
+        "pop_size": 50,
+        "r1": 2.35,
+    }
+    paras_improved_lco = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_qsa = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_saro = {
+        "epoch": 20,
+        "pop_size": 50,
+        "se": 0.5,
+        "mu": 15
+    }
+    paras_ssdo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_tlo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_improved_tlo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "n_teachers": 5,
+    }
 
-	paras_aoa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "alpha": 5,
-	    "miu": 0.5,
-	    "moa_min": 0.2,
-	    "moa_max": 0.9,
-	}
-	paras_cem = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "n_best": 20,
-	    "alpha": 0.7,
-	}
-	paras_cgo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_gbo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pr": 0.5,
-	    "beta_min": 0.2,
-	    "beta_max": 1.2,
-	}
-	paras_hc = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "neighbour_size": 50
-	}
-	paras_swarm_hc = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "neighbour_size": 10
-	}
-	paras_pss = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "acceptance_rate": 0.8,
-	    "sampling_method": "LHS",
-	}
-	paras_sca = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
+    paras_aoa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "alpha": 5,
+        "miu": 0.5,
+        "moa_min": 0.2,
+        "moa_max": 0.9,
+    }
+    paras_cem = {
+        "epoch": 20,
+        "pop_size": 50,
+        "n_best": 20,
+        "alpha": 0.7,
+    }
+    paras_cgo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_gbo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pr": 0.5,
+        "beta_min": 0.2,
+        "beta_max": 1.2,
+    }
+    paras_hc = {
+        "epoch": 20,
+        "pop_size": 50,
+        "neighbour_size": 50
+    }
+    paras_swarm_hc = {
+        "epoch": 20,
+        "pop_size": 50,
+        "neighbour_size": 10
+    }
+    paras_pss = {
+        "epoch": 20,
+        "pop_size": 50,
+        "acceptance_rate": 0.8,
+        "sampling_method": "LHS",
+    }
+    paras_sca = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
 
-	paras_hs = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "c_r": 0.95,
-	    "pa_r": 0.05
-	}
+    paras_hs = {
+        "epoch": 20,
+        "pop_size": 50,
+        "c_r": 0.95,
+        "pa_r": 0.05
+    }
 
-	paras_aeo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_gco = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "cr": 0.7,
-	    "wf": 1.25,
-	}
-	paras_wca = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "nsr": 4,
-	    "wc": 2.0,
-	    "dmax": 1e-6
-	}
+    paras_aeo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_gco = {
+        "epoch": 20,
+        "pop_size": 50,
+        "cr": 0.7,
+        "wf": 1.25,
+    }
+    paras_wca = {
+        "epoch": 20,
+        "pop_size": 50,
+        "nsr": 4,
+        "wc": 2.0,
+        "dmax": 1e-6
+    }
 
-	paras_archoa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "c1": 2,
-	    "c2": 5,
-	    "c3": 2,
-	    "c4": 0.5,
-	    "acc_max": 0.9,
-	    "acc_min": 0.1,
-	}
-	paras_aso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "alpha": 50,
-	    "beta": 0.2,
-	}
-	paras_efo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "r_rate": 0.3,
-	    "ps_rate": 0.85,
-	    "p_field": 0.1,
-	    "n_field": 0.45,
-	}
-	paras_eo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_hgso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "n_clusters": 3,
-	}
-	paras_mvo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "wep_min": 0.2,
-	    "wep_max": 1.0,
-	}
-	paras_nro = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_sa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "max_sub_iter": 5,
-	    "t0": 1000,
-	    "t1": 1,
-	    "move_count": 5,
-	    "mutation_rate": 0.1,
-	    "mutation_step_size": 0.1,
-	    "mutation_step_size_damp": 0.99,
-	}
-	paras_two = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_wdo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "RT": 3,
-	    "g_c": 0.2,
-	    "alp": 0.4,
-	    "c_e": 0.4,
-	    "max_v": 0.3,
-	}
+    paras_archoa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "c1": 2,
+        "c2": 5,
+        "c3": 2,
+        "c4": 0.5,
+        "acc_max": 0.9,
+        "acc_min": 0.1,
+    }
+    paras_aso = {
+        "epoch": 20,
+        "pop_size": 50,
+        "alpha": 50,
+        "beta": 0.2,
+    }
+    paras_efo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "r_rate": 0.3,
+        "ps_rate": 0.85,
+        "p_field": 0.1,
+        "n_field": 0.45,
+    }
+    paras_eo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_hgso = {
+        "epoch": 20,
+        "pop_size": 50,
+        "n_clusters": 3,
+    }
+    paras_mvo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "wep_min": 0.2,
+        "wep_max": 1.0,
+    }
+    paras_nro = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_sa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "max_sub_iter": 5,
+        "t0": 1000,
+        "t1": 1,
+        "move_count": 5,
+        "mutation_rate": 0.1,
+        "mutation_step_size": 0.1,
+        "mutation_step_size_damp": 0.99,
+    }
+    paras_two = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_wdo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "RT": 3,
+        "g_c": 0.2,
+        "alp": 0.4,
+        "c_e": 0.4,
+        "max_v": 0.3,
+    }
 
-	paras_abc = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "n_elites": 16,
-	    "n_others": 4,
-	    "patch_size": 5.0,
-	    "patch_reduction": 0.985,
-	    "n_sites": 3,
-	    "n_elite_sites": 1,
-	}
-	paras_acor = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "sample_count": 25,
-	    "intent_factor": 0.5,
-	    "zeta": 1.0,
-	}
-	paras_alo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_ao = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_ba = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "loudness": 0.8,
-	    "pulse_rate": 0.95,
-	    "pf_min": 0.,
-	    "pf_max": 10.,
-	}
-	paras_adaptive_ba = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "loudness_min": 1.0,
-	    "loudness_max": 2.0,
-	    "pr_min": 0.15,
-	    "pr_max": 0.85,
-	    "pf_min": 0.,
-	    "pf_max": 10.,
-	}
-	paras_modified_ba = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pulse_rate": 0.95,
-	    "pf_min": 0.,
-	    "pf_max": 10.,
-	}
-	paras_beesa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "selected_site_ratio": 0.5,
-	    "elite_site_ratio": 0.4,
-	    "selected_site_bee_ratio": 0.1,
-	    "elite_site_bee_ratio": 2.0,
-	    "dance_radius": 0.1,
-	    "dance_reduction": 0.99,
-	}
-	paras_prob_beesa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "recruited_bee_ratio": 0.1,
-	    "dance_radius": 0.1,
-	    "dance_reduction": 0.99,
-	}
-	paras_bes = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "a_factor": 10,
-	    "R_factor": 1.5,
-	    "alpha": 2.0,
-	    "c1": 2.0,
-	    "c2": 2.0,
-	}
-	paras_bfo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "Ci": 0.01,
-	    "Ped": 0.25,
-	    "Nc": 5,
-	    "Ns": 4,
-	    "d_attract": 0.1,
-	    "w_attract": 0.2,
-	    "h_repels": 0.1,
-	    "w_repels": 10,
-	}
-	paras_abfo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "C_s": 0.1,
-	    "C_e": 0.001,
-	    "Ped": 0.01,
-	    "Ns": 4,
-	    "N_adapt": 4,
-	    "N_split": 40,
-	}
-	paras_bsa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "ff": 10,
-	    "pff": 0.8,
-	    "c1": 1.5,
-	    "c2": 1.5,
-	    "a1": 1.0,
-	    "a2": 1.0,
-	    "fl": 0.5,
-	}
-	paras_coa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "n_coyotes": 5,
-	}
-	paras_csa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "p_a": 0.3,
-	}
-	paras_cso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "mixture_ratio": 0.15,
-	    "smp": 5,
-	    "spc": False,
-	    "cdc": 0.8,
-	    "srd": 0.15,
-	    "c1": 0.4,
-	    "w_min": 0.4,
-	    "w_max": 0.9,
-	    "selected_strategy": 1,
-	}
-	paras_do = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_eho = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "alpha": 0.5,
-	    "beta": 0.5,
-	    "n_clans": 5,
-	}
-	paras_fa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "max_sparks": 20,
-	    "p_a": 0.04,
-	    "p_b": 0.8,
-	    "max_ea": 40,
-	    "m_sparks": 5,
-	}
-	paras_ffa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "gamma": 0.001,
-	    "beta_base": 2,
-	    "alpha": 0.2,
-	    "alpha_damp": 0.99,
-	    "delta": 0.05,
-	    "exponent": 2,
-	}
-	paras_foa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_goa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "c_min": 0.00004,
-	    "c_max": 1.0,
-	}
-	paras_gwo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_hgs = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "PUP": 0.08,
-	    "LH": 10000,
-	}
-	paras_hho = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_ja = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_mfo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_mrfo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "somersault_range": 2.0,
-	}
-	paras_msa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "n_best": 5,
-	    "partition": 0.5,
-	    "max_step_size": 1.0,
-	}
-	paras_nmra = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pb": 0.75,
-	}
-	paras_improved_nmra = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pb": 0.75,
-	    "pm": 0.01,
-	}
-	paras_pfa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_pso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "c1": 2.05,
-	    "c2": 2.05,
-	    "w_min": 0.4,
-	    "w_max": 0.9,
-	}
-	paras_ppso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_hpso_tvac = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "ci": 0.5,
-	    "cf": 0.0,
-	}
-	paras_cpso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "c1": 2.05,
-	    "c2": 2.05,
-	    "w_min": 0.4,
-	    "w_max": 0.9,
-	}
-	paras_clpso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "c_local": 1.2,
-	    "w_min": 0.4,
-	    "w_max": 0.9,
-	    "max_flag": 7,
-	}
-	paras_sfo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pp": 0.1,
-	    "AP": 4.0,
-	    "epsilon": 0.0001,
-	}
-	paras_improved_sfo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "pp": 0.1,
-	}
-	paras_sho = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "h_factor": 5.0,
-	    "N_tried": 10,
-	}
-	paras_slo = paras_modified_slo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_improved_slo = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "c1": 1.2,
-	    "c2": 1.2
-	}
-	paras_srsr = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_ssa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "ST": 0.8,
-	    "PD": 0.2,
-	    "SD": 0.1,
-	}
-	paras_sso = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_sspidera = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "r_a": 1.0,
-	    "p_c": 0.7,
-	    "p_m": 0.1
-	}
-	paras_sspidero = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "fp_min": 0.65,
-	    "fp_max": 0.9
-	}
-	paras_woa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	}
-	paras_hi_woa = {
-	    "epoch": 20,
-	    "pop_size": 50,
-	    "feedback_max": 10
-	}
+    paras_abc = {
+        "epoch": 20,
+        "pop_size": 50,
+        "n_elites": 16,
+        "n_others": 4,
+        "patch_size": 5.0,
+        "patch_reduction": 0.985,
+        "n_sites": 3,
+        "n_elite_sites": 1,
+    }
+    paras_acor = {
+        "epoch": 20,
+        "pop_size": 50,
+        "sample_count": 25,
+        "intent_factor": 0.5,
+        "zeta": 1.0,
+    }
+    paras_alo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_ao = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_ba = {
+        "epoch": 20,
+        "pop_size": 50,
+        "loudness": 0.8,
+        "pulse_rate": 0.95,
+        "pf_min": 0.,
+        "pf_max": 10.,
+    }
+    paras_adaptive_ba = {
+        "epoch": 20,
+        "pop_size": 50,
+        "loudness_min": 1.0,
+        "loudness_max": 2.0,
+        "pr_min": 0.15,
+        "pr_max": 0.85,
+        "pf_min": 0.,
+        "pf_max": 10.,
+    }
+    paras_dev_ba = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pulse_rate": 0.95,
+        "pf_min": 0.,
+        "pf_max": 10.,
+    }
+    paras_beesa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "selected_site_ratio": 0.5,
+        "elite_site_ratio": 0.4,
+        "selected_site_bee_ratio": 0.1,
+        "elite_site_bee_ratio": 2.0,
+        "dance_radius": 0.1,
+        "dance_reduction": 0.99,
+    }
+    paras_prob_beesa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "recruited_bee_ratio": 0.1,
+        "dance_radius": 0.1,
+        "dance_reduction": 0.99,
+    }
+    paras_bes = {
+        "epoch": 20,
+        "pop_size": 50,
+        "a_factor": 10,
+        "R_factor": 1.5,
+        "alpha": 2.0,
+        "c1": 2.0,
+        "c2": 2.0,
+    }
+    paras_bfo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "Ci": 0.01,
+        "Ped": 0.25,
+        "Nc": 5,
+        "Ns": 4,
+        "d_attract": 0.1,
+        "w_attract": 0.2,
+        "h_repels": 0.1,
+        "w_repels": 10,
+    }
+    paras_abfo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "C_s": 0.1,
+        "C_e": 0.001,
+        "Ped": 0.01,
+        "Ns": 4,
+        "N_adapt": 4,
+        "N_split": 40,
+    }
+    paras_bsa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "ff": 10,
+        "pff": 0.8,
+        "c1": 1.5,
+        "c2": 1.5,
+        "a1": 1.0,
+        "a2": 1.0,
+        "fl": 0.5,
+    }
+    paras_coa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "n_coyotes": 5,
+    }
+    paras_csa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "p_a": 0.3,
+    }
+    paras_cso = {
+        "epoch": 20,
+        "pop_size": 50,
+        "mixture_ratio": 0.15,
+        "smp": 5,
+        "spc": False,
+        "cdc": 0.8,
+        "srd": 0.15,
+        "c1": 0.4,
+        "w_min": 0.4,
+        "w_max": 0.9,
+        "selected_strategy": 1,
+    }
+    paras_do = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_eho = {
+        "epoch": 20,
+        "pop_size": 50,
+        "alpha": 0.5,
+        "beta": 0.5,
+        "n_clans": 5,
+    }
+    paras_fa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "max_sparks": 20,
+        "p_a": 0.04,
+        "p_b": 0.8,
+        "max_ea": 40,
+        "m_sparks": 5,
+    }
+    paras_ffa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "gamma": 0.001,
+        "beta_base": 2,
+        "alpha": 0.2,
+        "alpha_damp": 0.99,
+        "delta": 0.05,
+        "exponent": 2,
+    }
+    paras_foa = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_goa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "c_min": 0.00004,
+        "c_max": 1.0,
+    }
+    paras_gwo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_hgs = {
+        "epoch": 20,
+        "pop_size": 50,
+        "PUP": 0.08,
+        "LH": 10000,
+    }
+    paras_hho = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_ja = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_mfo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_mrfo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "somersault_range": 2.0,
+    }
+    paras_msa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "n_best": 5,
+        "partition": 0.5,
+        "max_step_size": 1.0,
+    }
+    paras_nmra = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pb": 0.75,
+    }
+    paras_improved_nmra = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pb": 0.75,
+        "pm": 0.01,
+    }
+    paras_pfa = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_pso = {
+        "epoch": 20,
+        "pop_size": 50,
+        "c1": 2.05,
+        "c2": 2.05,
+        "w_min": 0.4,
+        "w_max": 0.9,
+    }
+    paras_ppso = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_hpso_tvac = {
+        "epoch": 20,
+        "pop_size": 50,
+        "ci": 0.5,
+        "cf": 0.0,
+    }
+    paras_cpso = {
+        "epoch": 20,
+        "pop_size": 50,
+        "c1": 2.05,
+        "c2": 2.05,
+        "w_min": 0.4,
+        "w_max": 0.9,
+    }
+    paras_clpso = {
+        "epoch": 20,
+        "pop_size": 50,
+        "c_local": 1.2,
+        "w_min": 0.4,
+        "w_max": 0.9,
+        "max_flag": 7,
+    }
+    paras_sfo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pp": 0.1,
+        "AP": 4.0,
+        "epsilon": 0.0001,
+    }
+    paras_improved_sfo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "pp": 0.1,
+    }
+    paras_sho = {
+        "epoch": 20,
+        "pop_size": 50,
+        "h_factor": 5.0,
+        "N_tried": 10,
+    }
+    paras_slo = paras_modified_slo = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_improved_slo = {
+        "epoch": 20,
+        "pop_size": 50,
+        "c1": 1.2,
+        "c2": 1.2
+    }
+    paras_srsr = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_ssa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "ST": 0.8,
+        "PD": 0.2,
+        "SD": 0.1,
+    }
+    paras_sso = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_sspidera = {
+        "epoch": 20,
+        "pop_size": 50,
+        "r_a": 1.0,
+        "p_c": 0.7,
+        "p_m": 0.1
+    }
+    paras_sspidero = {
+        "epoch": 20,
+        "pop_size": 50,
+        "fp_min": 0.65,
+        "fp_max": 0.9
+    }
+    paras_woa = {
+        "epoch": 20,
+        "pop_size": 50,
+    }
+    paras_hi_woa = {
+        "epoch": 20,
+        "pop_size": 50,
+        "feedback_max": 10
+    }
 
-	if __name__ == "__main__":
-	    model = BBO.BaseBBO(**paras_bbo)
-		model = BBO.OriginalBBO(**paras_bbo)
-		model = EOA.OriginalEOA(**paras_eoa)
-		model = IWO.OriginalIWO(**paras_eoa)
-		model = SBO.BaseSBO(**paras_sbo)
-		model = SBO.OriginalSBO(**paras_sbo)
-		model = SMA.BaseSMA(**paras_sma)
-		model = SMA.OriginalSMA(**paras_sma)
-		model = VCS.BaseVCS(**paras_vcs)
-		model = VCS.OriginalVCS(**paras_vcs)
-		model = WHO.OriginalWHO(**paras_vcs)
+    if __name__ == "__main__":
+            model = BBO.DevBBO(**paras_bbo)
+            model = BBO.OriginalBBO(**paras_bbo)
+            model = EOA.OriginalEOA(**paras_eoa)
+            model = IWO.OriginalIWO(**paras_eoa)
+            model = SBO.DevSBO(**paras_sbo)
+            model = SBO.OriginalSBO(**paras_sbo)
+            model = SMA.DevSMA(**paras_sma)
+            model = SMA.OriginalSMA(**paras_sma)
+            model = VCS.DevVCS(**paras_vcs)
+            model = VCS.OriginalVCS(**paras_vcs)
+            model = WHO.OriginalWHO(**paras_vcs)
 
-		model = CRO.OriginalCRO(**paras_cro)
-		model = CRO.OCRO(**paras_ocro)
-		model = DE.BaseDE(**paras_de)
-		model = DE.JADE(**paras_jade)
-		model = DE.SADE(**paras_sade)
-		model = DE.SHADE(**paras_shade)
-		model = DE.L_SHADE(**paras_lshade)
-		model = DE.SAP_DE(**paras_sap_de)
-		model = EP.OriginalEP(**paras_ep)
-		model = EP.LevyEP(**paras_levy_ep)
-		model = ES.OriginalES(**paras_ep)
-		model = ES.LevyES(**paras_levy_ep)
-		model = FPA.OriginalFPA(**paras_fpa)
-		model = GA.BaseGA(**paras_ga)
-		model = GA.SingleGA(**paras_single_ga)
-		model = GA.MultiGA(**paras_multi_ga)
-		model = MA.OriginalMA(**paras_ma)
+            model = CRO.OriginalCRO(**paras_cro)
+            model = CRO.OCRO(**paras_ocro)
+            # model = DE.BaseDE(**paras_de)
+            model = DE.JADE(**paras_jade)
+            model = DE.SADE(**paras_sade)
+            model = SHADE.OriginalSHADE(**paras_shade)
+            model = SHADE.L_SHADE(**paras_lshade)
+            model = DE.SAP_DE(**paras_sap_de)
+            model = EP.OriginalEP(**paras_ep)
+            model = EP.LevyEP(**paras_levy_ep)
+            model = ES.OriginalES(**paras_ep)
+            model = ES.LevyES(**paras_levy_ep)
+            model = FPA.OriginalFPA(**paras_fpa)
+            model = GA.BaseGA(**paras_ga)
+            model = GA.SingleGA(**paras_single_ga)
+            model = GA.MultiGA(**paras_multi_ga)
+            model = MA.OriginalMA(**paras_ma)
 
-		model = BRO.BaseBRO(**paras_bro)
-		model = BRO.OriginalBRO(**paras_bro)
-		model = BSO.OriginalBSO(**paras_bso)
-		model = BSO.ImprovedBSO(**paras_improved_bso)
-		model = CA.OriginalCA(**paras_ca)
-		model = CHIO.BaseCHIO(**paras_chio)
-		model = CHIO.OriginalCHIO(**paras_chio)
-		model = FBIO.BaseFBIO(**paras_fbio)
-		model = FBIO.OriginalFBIO(**paras_fbio)
-		model = GSKA.BaseGSKA(**paras_base_gska)
-		model = GSKA.OriginalGSKA(**paras_gska)
-		model = ICA.OriginalICA(**paras_ica)
-		model = LCO.BaseLCO(**paras_lco)
-		model = LCO.OriginalLCO(**paras_lco)
-		model = LCO.ImprovedLCO(**paras_improved_lco)
-		model = QSA.BaseQSA(**paras_qsa)
-		model = QSA.OriginalQSA(**paras_qsa)
-		model = QSA.OppoQSA(**paras_qsa)
-		model = QSA.LevyQSA(**paras_qsa)
-		model = QSA.ImprovedQSA(**paras_qsa)
-		model = SARO.BaseSARO(**paras_saro)
-		model = SARO.OriginalSARO(**paras_saro)
-		model = SSDO.OriginalSSDO(**paras_ssdo)
-		model = TLO.BaseTLO(**paras_tlo)
-		model = TLO.OriginalTLO(**paras_tlo)
-		model = TLO.ImprovedTLO(**paras_improved_tlo)
+            model = BRO.DevBRO(**paras_bro)
+            model = BRO.OriginalBRO(**paras_bro)
+            model = BSO.OriginalBSO(**paras_bso)
+            model = BSO.ImprovedBSO(**paras_improved_bso)
+            model = CA.OriginalCA(**paras_ca)
+            model = CHIO.DevCHIO(**paras_chio)
+            model = CHIO.OriginalCHIO(**paras_chio)
+            model = FBIO.DevFBIO(**paras_fbio)
+            model = FBIO.OriginalFBIO(**paras_fbio)
+            model = GSKA.DevGSKA(**paras_base_gska)
+            model = GSKA.OriginalGSKA(**paras_gska)
+            model = ICA.OriginalICA(**paras_ica)
+            model = LCO.DevLCO(**paras_lco)
+            model = LCO.OriginalLCO(**paras_lco)
+            model = LCO.ImprovedLCO(**paras_improved_lco)
+            model = QSA.DevQSA(**paras_qsa)
+            model = QSA.OriginalQSA(**paras_qsa)
+            model = QSA.OppoQSA(**paras_qsa)
+            model = QSA.LevyQSA(**paras_qsa)
+            model = QSA.ImprovedQSA(**paras_qsa)
+            model = SARO.DevSARO(**paras_saro)
+            model = SARO.OriginalSARO(**paras_saro)
+            model = SSDO.OriginalSSDO(**paras_ssdo)
+            model = TLO.DevTLO(**paras_tlo)
+            model = TLO.OriginalTLO(**paras_tlo)
+            model = TLO.ImprovedTLO(**paras_improved_tlo)
 
-		model = AOA.OriginalAOA(**paras_aoa)
-		model = CEM.OriginalCEM(**paras_cem)
-		model = CGO.OriginalCGO(**paras_cgo)
-		model = GBO.OriginalGBO(**paras_gbo)
-		model = HC.OriginalHC(**paras_hc)
-		model = HC.SwarmHC(**paras_swarm_hc)
-		model = PSS.OriginalPSS(**paras_pss)
-		model = SCA.OriginalSCA(**paras_sca)
-		model = SCA.BaseSCA(**paras_sca)
+            model = AOA.OriginalAOA(**paras_aoa)
+            model = CEM.OriginalCEM(**paras_cem)
+            model = CGO.OriginalCGO(**paras_cgo)
+            model = GBO.OriginalGBO(**paras_gbo)
+            model = HC.OriginalHC(**paras_hc)
+            model = HC.SwarmHC(**paras_swarm_hc)
+            model = PSS.OriginalPSS(**paras_pss)
+            model = SCA.OriginalSCA(**paras_sca)
+            model = SCA.DevSCA(**paras_sca)
 
-		model = HS.BaseHS(**paras_hs)
-		model = HS.OriginalHS(**paras_hs)
+            model = HS.DevHS(**paras_hs)
+            model = HS.OriginalHS(**paras_hs)
 
-		model = AEO.OriginalAEO(**paras_aeo)
-		model = AEO.EnhancedAEO(**paras_aeo)
-		model = AEO.ModifiedAEO(**paras_aeo)
-		model = AEO.ImprovedAEO(**paras_aeo)
-		model = AEO.AugmentedAEO(**paras_aeo)
-		model = GCO.BaseGCO(**paras_aeo)
-		model = GCO.OriginalGCO(**paras_aeo)
-		model = WCA.OriginalWCA(**paras_wca)
+            model = AEO.OriginalAEO(**paras_aeo)
+            model = AEO.EnhancedAEO(**paras_aeo)
+            model = AEO.ModifiedAEO(**paras_aeo)
+            model = AEO.ImprovedAEO(**paras_aeo)
+            model = AEO.AugmentedAEO(**paras_aeo)
+            model = GCO.DevGCO(**paras_aeo)
+            model = GCO.OriginalGCO(**paras_aeo)
+            model = WCA.OriginalWCA(**paras_wca)
 
-		model = ArchOA.OriginalArchOA(**paras_archoa)
-		model = ASO.OriginalASO(**paras_aso)
-		model = EFO.OriginalEFO(**paras_efo)
-		model = EFO.BaseEFO(**paras_efo)
-		model = EO.OriginalEO(**paras_eo)
-		model = EO.AdaptiveEO(**paras_eo)
-		model = EO.ModifiedEO(**paras_eo)
-		model = HGSO.OriginalHGSO(**paras_hgso)
-		model = MVO.OriginalMVO(**paras_mvo)
-		model = NRO.OriginalNRO(**paras_nro)
-		model = SA.OriginalSA(**paras_sa)
-		model = SA.SwarmSA(**paras_sa)
-		model = SA.GaussianSA(**paras_sa)
-		model = TWO.OriginalTWO(**paras_two)
-		model = TWO.OppoTWO(**paras_two)
-		model = TWO.LevyTWO(**paras_two)
-		model = TWO.EnhancedTWO(**paras_two)
-		model = WDO.OriginalWDO(**paras_wdo)
+            model = ArchOA.OriginalArchOA(**paras_archoa)
+            model = ASO.OriginalASO(**paras_aso)
+            model = EFO.OriginalEFO(**paras_efo)
+            model = EFO.DevEFO(**paras_efo)
+            model = EO.OriginalEO(**paras_eo)
+            model = EO.AdaptiveEO(**paras_eo)
+            model = EO.ModifiedEO(**paras_eo)
+            model = HGSO.OriginalHGSO(**paras_hgso)
+            model = MVO.OriginalMVO(**paras_mvo)
+            model = NRO.OriginalNRO(**paras_nro)
+            model = SA.OriginalSA(**paras_sa)
+            model = SA.SwarmSA(**paras_sa)
+            model = SA.GaussianSA(**paras_sa)
+            model = TWO.OriginalTWO(**paras_two)
+            model = TWO.OppoTWO(**paras_two)
+            model = TWO.LevyTWO(**paras_two)
+            model = TWO.EnhancedTWO(**paras_two)
+            model = WDO.OriginalWDO(**paras_wdo)
 
-		model = ABC.OriginalABC(**paras_abc)
-		model = ACOR.OriginalACOR(**paras_acor)
-		model = ALO.OriginalALO(**paras_alo)
-		model = AO.OriginalAO(**paras_ao)
-		model = ALO.BaseALO(**paras_alo)
-		model = BA.OriginalBA(**paras_ba)
-		model = BA.AdaptiveBA(**paras_adaptive_ba)
-		model = BA.ModifiedBA(**paras_modified_ba)
-		model = BeesA.OriginalBeesA(**paras_beesa)
-		model = BeesA.ProbBeesA(**paras_prob_beesa)
-		model = BES.OriginalBES(**paras_bes)
-		model = BFO.OriginalBFO(**paras_bfo)
-		model = BFO.ABFO(**paras_abfo)
-		model = BSA.OriginalBSA(**paras_bsa)
-		model = COA.OriginalCOA(**paras_coa)
-		model = CSA.OriginalCSA(**paras_csa)
-		model = CSO.OriginalCSO(**paras_cso)
-		model = DO.OriginalDO(**paras_do)
-		model = EHO.OriginalEHO(**paras_eho)
-		model = FA.OriginalFA(**paras_fa)
-		model = FFA.OriginalFFA(**paras_ffa)
-		model = FOA.OriginalFOA(**paras_foa)
-		model = FOA.BaseFOA(**paras_foa)
-		model = FOA.WhaleFOA(**paras_foa)
-		model = GOA.OriginalGOA(**paras_goa)
-		model = GWO.OriginalGWO(**paras_gwo)
-		model = GWO.RW_GWO(**paras_gwo)
-		model = HGS.OriginalHGS(**paras_hgs)
-		model = HHO.OriginalHHO(**paras_hho)
-		model = JA.OriginalJA(**paras_ja)
-		model = JA.BaseJA(**paras_ja)
-		model = JA.LevyJA(**paras_ja)
-		model = MFO.OriginalMFO(**paras_mfo)
-		model = MFO.BaseMFO(**paras_mfo)
-		model = MRFO.OriginalMRFO(**paras_mrfo)
-		model = MSA.OriginalMSA(**paras_msa)
-		model = NMRA.ImprovedNMRA(**paras_improved_nmra)
-		model = NMRA.OriginalNMRA(**paras_nmra)
-		model = PFA.OriginalPFA(**paras_pfa)
-		model = PSO.OriginalPSO(**paras_pso)
-		model = PSO.PPSO(**paras_ppso)
-		model = PSO.HPSO_TVAC(**paras_hpso_tvac)
-		model = PSO.C_PSO(**paras_cpso)
-		model = PSO.CL_PSO(**paras_clpso)
-		model = SFO.OriginalSFO(**paras_sfo)
-		model = SFO.ImprovedSFO(**paras_improved_sfo)
-		model = SHO.OriginalSHO(**paras_sho)
-		model = SLO.OriginalSLO(**paras_slo)
-		model = SLO.ModifiedSLO(**paras_modified_slo)
-		model = SLO.ImprovedSLO(**paras_improved_slo)
-		model = SRSR.OriginalSRSR(**paras_srsr)
-		model = SSA.OriginalSSA(**paras_ssa)
-		model = SSA.BaseSSA(**paras_ssa)
-		model = SSO.OriginalSSO(**paras_sso)
-		model = SSpiderA.OriginalSSpiderA(**paras_sspidera)
-		model = SSpiderO.OriginalSSpiderO(**paras_sspidero)
-		model = WOA.OriginalWOA(**paras_woa)
-		model = WOA.HI_WOA(**paras_hi_woa)
+            model = ABC.OriginalABC(**paras_abc)
+            model = ACOR.OriginalACOR(**paras_acor)
+            model = ALO.OriginalALO(**paras_alo)
+            model = AO.OriginalAO(**paras_ao)
+            model = ALO.DevALO(**paras_alo)
+            model = BA.OriginalBA(**paras_ba)
+            model = BA.AdaptiveBA(**paras_adaptive_ba)
+            model = BA.DevBA(**paras_dev_ba)
+            model = BeesA.OriginalBeesA(**paras_beesa)
+            model = BeesA.ProbBeesA(**paras_prob_beesa)
+            model = BES.OriginalBES(**paras_bes)
+            model = BFO.OriginalBFO(**paras_bfo)
+            model = BFO.ABFO(**paras_abfo)
+            model = BSA.OriginalBSA(**paras_bsa)
+            model = COA.OriginalCOA(**paras_coa)
+            model = CSA.OriginalCSA(**paras_csa)
+            model = CSO.OriginalCSO(**paras_cso)
+            model = DO.OriginalDO(**paras_do)
+            model = EHO.OriginalEHO(**paras_eho)
+            model = FA.OriginalFA(**paras_fa)
+            model = FFA.OriginalFFA(**paras_ffa)
+            model = FOA.OriginalFOA(**paras_foa)
+            model = FOA.DevFOA(**paras_foa)
+            model = FOA.WhaleFOA(**paras_foa)
+            model = GOA.OriginalGOA(**paras_goa)
+            model = GWO.OriginalGWO(**paras_gwo)
+            model = GWO.RW_GWO(**paras_gwo)
+            model = HGS.OriginalHGS(**paras_hgs)
+            model = HHO.OriginalHHO(**paras_hho)
+            model = JA.OriginalJA(**paras_ja)
+            model = JA.DevJA(**paras_ja)
+            model = JA.LevyJA(**paras_ja)
+            model = MFO.OriginalMFO(**paras_mfo)
+            # model = MFO.BaseMFO(**paras_mfo)
+            model = MRFO.OriginalMRFO(**paras_mrfo)
+            model = MSA.OriginalMSA(**paras_msa)
+            model = NMRA.ImprovedNMRA(**paras_improved_nmra)
+            model = NMRA.OriginalNMRA(**paras_nmra)
+            model = PFA.OriginalPFA(**paras_pfa)
+            model = PSO.OriginalPSO(**paras_pso)
+            model = PSO.P_PSO(**paras_ppso)
+            model = PSO.HPSO_TVAC(**paras_hpso_tvac)
+            model = PSO.C_PSO(**paras_cpso)
+            model = PSO.CL_PSO(**paras_clpso)
+            model = SFO.OriginalSFO(**paras_sfo)
+            model = SFO.ImprovedSFO(**paras_improved_sfo)
+            model = SHO.OriginalSHO(**paras_sho)
+            model = SLO.OriginalSLO(**paras_slo)
+            model = SLO.ModifiedSLO(**paras_modified_slo)
+            model = SLO.ImprovedSLO(**paras_improved_slo)
+            model = SRSR.OriginalSRSR(**paras_srsr)
+            model = SSA.OriginalSSA(**paras_ssa)
+            model = SSA.DevSSA(**paras_ssa)
+            model = SSO.OriginalSSO(**paras_sso)
+            model = SSpiderA.OriginalSSpiderA(**paras_sspidera)
+            model = SSpiderO.OriginalSSpiderO(**paras_sspidero)
+            model = WOA.OriginalWOA(**paras_woa)
+            model = WOA.HI_WOA(**paras_hi_woa)
 
-		best_position, best_fitness = model.solve(P1)
-		print(model.get_parameters())
-		print(model.get_name())
-		print(model.problem.get_name())
-		print(model.get_attributes()["g_best"])
+            g_best = model.solve(problem)
+            print(model.get_parameters())
+            print(model.get_name())
+            print(model.problem.get_name())
+            print(model.get_attributes()["g_best"])
 
 
 .. toctree::
diff --git a/examples/applications/pytorch/linear_regression.py b/examples/applications/pytorch/linear_regression.py
index bae747ef..d0279da2 100644
--- a/examples/applications/pytorch/linear_regression.py
+++ b/examples/applications/pytorch/linear_regression.py
@@ -26,7 +26,7 @@ def __init__(self, bounds, minmax="min", data=None, **kwargs):
         self.data = data
         super().__init__(bounds, minmax, **kwargs)
 
-    def fit_func(self, x: np.ndarray):
+    def obj_func(self, x: np.ndarray):
         # Decode solution from real value to real-world solution
         x = self.decode_solution(x)
         opt, learning_rate, epoch = x["optimizer"], x["learning-rate"], x["epoch"]
diff --git a/examples/run_all_parameters.py b/examples/run_all_parameters.py
index c82e58e4..9957a48c 100644
--- a/examples/run_all_parameters.py
+++ b/examples/run_all_parameters.py
@@ -5,8 +5,9 @@
 # --------------------------------------------------%
 
 from opfunu.cec_based.cec2017 import F292017
+from mealpy import FloatVar
 from mealpy.bio_based import BBO, EOA, IWO, SBO, SMA, TPO, VCS, WHO
-from mealpy.evolutionary_based import CRO, DE, EP, ES, FPA, GA, MA
+from mealpy.evolutionary_based import CRO, DE, EP, ES, FPA, GA, MA, SHADE
 from mealpy.human_based import BRO, BSO, CA, CHIO, FBIO, GSKA, ICA, LCO, QSA, SARO, SSDO, TLO
 from mealpy.math_based import AOA, CEM, CGO, GBO, HC, PSS, SCA
 from mealpy.music_based import HS
@@ -18,9 +19,8 @@
 
 f18 = F292017(ndim=30, f_bias=0)
 P1 = {
-    "fit_func": f18.evaluate,
-    "lb": f18.lb,
-    "ub": f18.ub,
+    "obj_func": f18.evaluate,
+    "bounds": FloatVar(lb=f18.lb, ub=f18.ub, name="delta"),
     "minmax": "min",
     "name": "F18"
 }
@@ -727,25 +727,25 @@
 }
 
 
-model = BBO.BaseBBO(**paras_bbo)
+model = BBO.DevBBO(**paras_bbo)
 model = BBO.OriginalBBO(**paras_bbo)
 model = EOA.OriginalEOA(**paras_eoa)
 model = IWO.OriginalIWO(**paras_eoa)
-model = SBO.BaseSBO(**paras_sbo)
+model = SBO.DevSBO(**paras_sbo)
 model = SBO.OriginalSBO(**paras_sbo)
-model = SMA.BaseSMA(**paras_sma)
+model = SMA.DevSMA(**paras_sma)
 model = SMA.OriginalSMA(**paras_sma)
-model = VCS.BaseVCS(**paras_vcs)
+model = VCS.DevVCS(**paras_vcs)
 model = VCS.OriginalVCS(**paras_vcs)
 model = WHO.OriginalWHO(**paras_vcs)
 
 model = CRO.OriginalCRO(**paras_cro)
 model = CRO.OCRO(**paras_ocro)
-model = DE.BaseDE(**paras_de)
+# model = DE.BaseDE(**paras_de)
 model = DE.JADE(**paras_jade)
 model = DE.SADE(**paras_sade)
-model = DE.SHADE(**paras_shade)
-model = DE.L_SHADE(**paras_lshade)
+model = SHADE.OriginalSHADE(**paras_shade)
+model = SHADE.L_SHADE(**paras_lshade)
 model = DE.SAP_DE(**paras_sap_de)
 model = EP.OriginalEP(**paras_ep)
 model = EP.LevyEP(**paras_levy_ep)
@@ -757,30 +757,30 @@
 model = GA.MultiGA(**paras_multi_ga)
 model = MA.OriginalMA(**paras_ma)
 
-model = BRO.BaseBRO(**paras_bro)
+model = BRO.DevBRO(**paras_bro)
 model = BRO.OriginalBRO(**paras_bro)
 model = BSO.OriginalBSO(**paras_bso)
 model = BSO.ImprovedBSO(**paras_improved_bso)
 model = CA.OriginalCA(**paras_ca)
-model = CHIO.BaseCHIO(**paras_chio)
+model = CHIO.DevCHIO(**paras_chio)
 model = CHIO.OriginalCHIO(**paras_chio)
-model = FBIO.BaseFBIO(**paras_fbio)
+model = FBIO.DevFBIO(**paras_fbio)
 model = FBIO.OriginalFBIO(**paras_fbio)
-model = GSKA.BaseGSKA(**paras_base_gska)
+model = GSKA.DevGSKA(**paras_base_gska)
 model = GSKA.OriginalGSKA(**paras_gska)
 model = ICA.OriginalICA(**paras_ica)
-model = LCO.BaseLCO(**paras_lco)
+model = LCO.DevLCO(**paras_lco)
 model = LCO.OriginalLCO(**paras_lco)
 model = LCO.ImprovedLCO(**paras_improved_lco)
-model = QSA.BaseQSA(**paras_qsa)
+model = QSA.DevQSA(**paras_qsa)
 model = QSA.OriginalQSA(**paras_qsa)
 model = QSA.OppoQSA(**paras_qsa)
 model = QSA.LevyQSA(**paras_qsa)
 model = QSA.ImprovedQSA(**paras_qsa)
-model = SARO.BaseSARO(**paras_saro)
+model = SARO.DevSARO(**paras_saro)
 model = SARO.OriginalSARO(**paras_saro)
 model = SSDO.OriginalSSDO(**paras_ssdo)
-model = TLO.BaseTLO(**paras_tlo)
+model = TLO.DevTLO(**paras_tlo)
 model = TLO.OriginalTLO(**paras_tlo)
 model = TLO.ImprovedTLO(**paras_improved_tlo)
 
@@ -792,9 +792,9 @@
 model = HC.SwarmHC(**paras_swarm_hc)
 model = PSS.OriginalPSS(**paras_pss)
 model = SCA.OriginalSCA(**paras_sca)
-model = SCA.BaseSCA(**paras_sca)
+model = SCA.DevSCA(**paras_sca)
 
-model = HS.BaseHS(**paras_hs)
+model = HS.DevHS(**paras_hs)
 model = HS.OriginalHS(**paras_hs)
 
 model = AEO.OriginalAEO(**paras_aeo)
@@ -802,14 +802,14 @@
 model = AEO.ModifiedAEO(**paras_aeo)
 model = AEO.ImprovedAEO(**paras_aeo)
 model = AEO.AugmentedAEO(**paras_aeo)
-model = GCO.BaseGCO(**paras_aeo)
+model = GCO.DevGCO(**paras_aeo)
 model = GCO.OriginalGCO(**paras_aeo)
 model = WCA.OriginalWCA(**paras_wca)
 
 model = ArchOA.OriginalArchOA(**paras_archoa)
 model = ASO.OriginalASO(**paras_aso)
 model = EFO.OriginalEFO(**paras_efo)
-model = EFO.BaseEFO(**paras_efo)
+model = EFO.DevEFO(**paras_efo)
 model = EO.OriginalEO(**paras_eo)
 model = EO.AdaptiveEO(**paras_eo)
 model = EO.ModifiedEO(**paras_eo)
@@ -828,10 +828,10 @@
 model = ACOR.OriginalACOR(**paras_acor)
 model = ALO.OriginalALO(**paras_alo)
 model = AO.OriginalAO(**paras_ao)
-model = ALO.BaseALO(**paras_alo)
+model = ALO.DevALO(**paras_alo)
 model = BA.OriginalBA(**paras_ba)
 model = BA.AdaptiveBA(**paras_adaptive_ba)
-model = BA.ModifiedBA(**paras_modified_ba)
+model = BA.DevBA(**paras_modified_ba)
 model = BeesA.OriginalBeesA(**paras_beesa)
 model = BeesA.ProbBeesA(**paras_prob_beesa)
 model = BES.OriginalBES(**paras_bes)
@@ -846,7 +846,7 @@
 model = FA.OriginalFA(**paras_fa)
 model = FFA.OriginalFFA(**paras_ffa)
 model = FOA.OriginalFOA(**paras_foa)
-model = FOA.BaseFOA(**paras_foa)
+model = FOA.DevFOA(**paras_foa)
 model = FOA.WhaleFOA(**paras_foa)
 model = GOA.OriginalGOA(**paras_goa)
 model = GWO.OriginalGWO(**paras_gwo)
@@ -854,17 +854,17 @@
 model = HGS.OriginalHGS(**paras_hgs)
 model = HHO.OriginalHHO(**paras_hho)
 model = JA.OriginalJA(**paras_ja)
-model = JA.BaseJA(**paras_ja)
+model = JA.DevJA(**paras_ja)
 model = JA.LevyJA(**paras_ja)
 model = MFO.OriginalMFO(**paras_mfo)
-model = MFO.BaseMFO(**paras_mfo)
+# model = MFO.BaseMFO(**paras_mfo)
 model = MRFO.OriginalMRFO(**paras_mrfo)
 model = MSA.OriginalMSA(**paras_msa)
 model = NMRA.ImprovedNMRA(**paras_improved_nmra)
 model = NMRA.OriginalNMRA(**paras_nmra)
 model = PFA.OriginalPFA(**paras_pfa)
 model = PSO.OriginalPSO(**paras_pso)
-model = PSO.PPSO(**paras_ppso)
+model = PSO.P_PSO(**paras_ppso)
 model = PSO.HPSO_TVAC(**paras_hpso_tvac)
 model = PSO.C_PSO(**paras_cpso)
 model = PSO.CL_PSO(**paras_clpso)
@@ -876,15 +876,15 @@
 model = SLO.ImprovedSLO(**paras_improved_slo)
 model = SRSR.OriginalSRSR(**paras_srsr)
 model = SSA.OriginalSSA(**paras_ssa)
-model = SSA.BaseSSA(**paras_ssa)
+model = SSA.DevSSA(**paras_ssa)
 model = SSO.OriginalSSO(**paras_sso)
 model = SSpiderA.OriginalSSpiderA(**paras_sspidera)
 model = SSpiderO.OriginalSSpiderO(**paras_sspidero)
 model = WOA.OriginalWOA(**paras_woa)
 model = WOA.HI_WOA(**paras_hi_woa)
 
-best_position, best_fitness = model.solve(P1)
+g_best = model.solve(P1)
 print(model.get_parameters())
 print(model.get_name())
 print(model.problem.get_name())
-print(model.get_attributes()["solution"])
+print(g_best)
\ No newline at end of file

From fbf846e4adef89e4084cf91d83cbf9cf82f80916 Mon Sep 17 00:00:00 2001
From: Godot <30374962+Godot115@users.noreply.github.com>
Date: Mon, 15 Apr 2024 06:26:12 +0800
Subject: [PATCH 2/3] Update import_all_models.rst

---
 .../general/advances/import_all_models.rst    | 1776 ++++++++---------
 1 file changed, 888 insertions(+), 888 deletions(-)

diff --git a/docs/source/pages/general/advances/import_all_models.rst b/docs/source/pages/general/advances/import_all_models.rst
index 8e61fd85..3b72131f 100644
--- a/docs/source/pages/general/advances/import_all_models.rst
+++ b/docs/source/pages/general/advances/import_all_models.rst
@@ -3,894 +3,894 @@ Import All Models
 
 .. code-block:: python
 
-    from mealpy import BBO, PSO, GA, ALO, AO, ARO, AVOA, BA, BBOA, BMO, EOA, IWO
-    from mealpy import SBO, SMA, SOA, SOS, TPO, TSA, VCS, WHO, AOA, CEM, CGO, CircleSA, GBO, HC, INFO, PSS, RUN, SCA
-    from mealpy import SHIO, TS, HS, AEO, GCO, WCA, CRO, DE, EP, ES, FPA, MA, SHADE, BRO, BSO, CA, CHIO, FBIO, GSKA, HBO
-    from mealpy import HCO, ICA, LCO, WarSO, TOA, TLO, SSDO, SPBO, SARO, QSA, ArchOA, ASO, CDO, EFO, EO, EVO, FLA
-    from mealpy import HGSO, MVO, NRO, RIME, SA, WDO, TWO, ABC, ACOR, AGTO, BeesA, BES, BFO, ZOA, WOA, WaOA, TSO
-    from mealpy import TDO, STO, SSpiderO, SSpiderA, SSO, SSA, SRSR, SLO, SHO, SFO, ServalOA, SeaHO, SCSO, POA
-    from mealpy import PFA, OOA, NGO, NMRA, MSA, MRFO, MPA, MGO, MFO, JA, HHO, HGS, HBA, GWO, GTO, GOA
-    from mealpy import GJO, FOX, FOA, FFO, FFA, FA, ESOA, EHO, DO, DMOA, CSO, CSA, CoatiOA, COA, BSA
-    from mealpy import StringVar, FloatVar, BoolVar, PermutationVar, MixedSetVar, IntegerVar, BinaryVar
-    from mealpy import Tuner, Multitask, Problem, Optimizer, Termination, ParameterGrid
-    from mealpy import get_all_optimizers, get_optimizer_by_name
-    import numpy as np
-
-    def objective_function(solution):
-        return np.sum(solution ** 2)
-
-    problem = {
-        "obj_func": objective_function,
-        "bounds": FloatVar(lb=[-3] * 20, ub=[5] * 20),
-        "name": "Squared Problem",
-        "log_to": "file",
-        "log_file": "results.log"
-    }
-
-    paras_bbo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "p_m": 0.01,
-        "elites": 2,
-    }
-    paras_eoa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "p_c": 0.9,
-        "p_m": 0.01,
-        "n_best": 2,
-        "alpha": 0.98,
-        "beta": 0.9,
-        "gamma": 0.9,
-    }
-    paras_iwo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "seed_min": 3,
-        "seed_max": 9,
-        "exponent": 3,
-        "sigma_start": 0.6,
-        "sigma_end": 0.01,
-    }
-    paras_sbo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "alpha": 0.9,
-        "p_m": 0.05,
-        "psw": 0.02,
-    }
-    paras_sma = {
-        "epoch": 20,
-        "pop_size": 50,
-        "p_t": 0.03,
-    }
-    paras_vcs = {
-        "epoch": 20,
-        "pop_size": 50,
-        "lamda": 0.5,
-        "sigma": 0.3,
-    }
-    paras_who = {
-        "epoch": 20,
-        "pop_size": 50,
-        "n_explore_step": 3,
-        "n_exploit_step": 3,
-        "eta": 0.15,
-        "p_hi": 0.9,
-        "local_alpha": 0.9,
-        "local_beta": 0.3,
-        "global_alpha": 0.2,
-        "global_beta": 0.8,
-        "delta_w": 2.0,
-        "delta_c": 2.0,
-    }
-    paras_cro = {
-        "epoch": 20,
-        "pop_size": 50,
-        "po": 0.4,
-        "Fb": 0.9,
-        "Fa": 0.1,
-        "Fd": 0.1,
-        "Pd": 0.5,
-        "GCR": 0.1,
-        "gamma_min": 0.02,
-        "gamma_max": 0.2,
-        "n_trials": 5,
-    }
-    paras_ocro = dict(paras_cro)
-    paras_ocro["restart_count"] = 5
-
-    paras_de = {
-        "epoch": 20,
-        "pop_size": 50,
-        "wf": 0.7,
-        "cr": 0.9,
-        "strategy": 0,
-    }
-    paras_jade = {
-        "epoch": 20,
-        "pop_size": 50,
-        "miu_f": 0.5,
-        "miu_cr": 0.5,
-        "pt": 0.1,
-        "ap": 0.1,
-    }
-    paras_sade = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_shade = paras_lshade = {
-        "epoch": 20,
-        "pop_size": 50,
-        "miu_f": 0.5,
-        "miu_cr": 0.5,
-    }
-    paras_sap_de = {
-        "epoch": 20,
-        "pop_size": 50,
-        "branch": "ABS"
-    }
-    paras_ep = paras_levy_ep = {
-        "epoch": 20,
-        "pop_size": 50,
-        "bout_size": 0.05
-    }
-    paras_es = paras_levy_es = {
-        "epoch": 20,
-        "pop_size": 50,
-        "lamda": 0.75
-    }
-    paras_fpa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "p_s": 0.8,
-        "levy_multiplier": 0.2
-    }
-    paras_ga = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pc": 0.9,
-        "pm": 0.05,
-    }
-    paras_single_ga = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pc": 0.9,
-        "pm": 0.8,
-        "selection": "roulette",
-        "crossover": "uniform",
-        "mutation": "swap",
-    }
-    paras_multi_ga = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pc": 0.9,
-        "pm": 0.05,
-        "selection": "roulette",
-        "crossover": "uniform",
-        "mutation": "swap",
-    }
-    paras_ma = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pc": 0.85,
-        "pm": 0.15,
-        "p_local": 0.5,
-        "max_local_gens": 10,
-        "bits_per_param": 4,
-    }
-
-    paras_bro = {
-        "epoch": 20,
-        "pop_size": 50,
-        "threshold": 3,
-    }
-    paras_improved_bso = {
-        "epoch": 20,
-        "pop_size": 50,
-        "m_clusters": 5,
-        "p1": 0.2,
-        "p2": 0.8,
-        "p3": 0.4,
-        "p4": 0.5,
-    }
-    paras_bso = dict(paras_improved_bso)
-    paras_bso["slope"] = 20
-    paras_ca = {
-        "epoch": 20,
-        "pop_size": 50,
-        "accepted_rate": 0.15,
-    }
-    paras_chio = {
-        "epoch": 20,
-        "pop_size": 50,
-        "brr": 0.15,
-        "max_age": 3
-    }
-    paras_fbio = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_base_gska = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pb": 0.1,
-        "kr": 0.9,
-    }
-    paras_gska = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pb": 0.1,
-        "kf": 0.5,
-        "kr": 0.9,
-        "kg": 5,
-    }
-    paras_ica = {
-        "epoch": 20,
-        "pop_size": 50,
-        "empire_count": 5,
-        "assimilation_coeff": 1.5,
-        "revolution_prob": 0.05,
-        "revolution_rate": 0.1,
-        "revolution_step_size": 0.1,
-        "zeta": 0.1,
-    }
-    paras_lco = {
-        "epoch": 20,
-        "pop_size": 50,
-        "r1": 2.35,
-    }
-    paras_improved_lco = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_qsa = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_saro = {
-        "epoch": 20,
-        "pop_size": 50,
-        "se": 0.5,
-        "mu": 15
-    }
-    paras_ssdo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_tlo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_improved_tlo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "n_teachers": 5,
-    }
-
-    paras_aoa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "alpha": 5,
-        "miu": 0.5,
-        "moa_min": 0.2,
-        "moa_max": 0.9,
-    }
-    paras_cem = {
-        "epoch": 20,
-        "pop_size": 50,
-        "n_best": 20,
-        "alpha": 0.7,
-    }
-    paras_cgo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_gbo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pr": 0.5,
-        "beta_min": 0.2,
-        "beta_max": 1.2,
-    }
-    paras_hc = {
-        "epoch": 20,
-        "pop_size": 50,
-        "neighbour_size": 50
-    }
-    paras_swarm_hc = {
-        "epoch": 20,
-        "pop_size": 50,
-        "neighbour_size": 10
-    }
-    paras_pss = {
-        "epoch": 20,
-        "pop_size": 50,
-        "acceptance_rate": 0.8,
-        "sampling_method": "LHS",
-    }
-    paras_sca = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-
-    paras_hs = {
-        "epoch": 20,
-        "pop_size": 50,
-        "c_r": 0.95,
-        "pa_r": 0.05
-    }
-
-    paras_aeo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_gco = {
-        "epoch": 20,
-        "pop_size": 50,
-        "cr": 0.7,
-        "wf": 1.25,
-    }
-    paras_wca = {
-        "epoch": 20,
-        "pop_size": 50,
-        "nsr": 4,
-        "wc": 2.0,
-        "dmax": 1e-6
-    }
-
-    paras_archoa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "c1": 2,
-        "c2": 5,
-        "c3": 2,
-        "c4": 0.5,
-        "acc_max": 0.9,
-        "acc_min": 0.1,
-    }
-    paras_aso = {
-        "epoch": 20,
-        "pop_size": 50,
-        "alpha": 50,
-        "beta": 0.2,
-    }
-    paras_efo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "r_rate": 0.3,
-        "ps_rate": 0.85,
-        "p_field": 0.1,
-        "n_field": 0.45,
-    }
-    paras_eo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_hgso = {
-        "epoch": 20,
-        "pop_size": 50,
-        "n_clusters": 3,
-    }
-    paras_mvo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "wep_min": 0.2,
-        "wep_max": 1.0,
-    }
-    paras_nro = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_sa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "max_sub_iter": 5,
-        "t0": 1000,
-        "t1": 1,
-        "move_count": 5,
-        "mutation_rate": 0.1,
-        "mutation_step_size": 0.1,
-        "mutation_step_size_damp": 0.99,
-    }
-    paras_two = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_wdo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "RT": 3,
-        "g_c": 0.2,
-        "alp": 0.4,
-        "c_e": 0.4,
-        "max_v": 0.3,
-    }
-
-    paras_abc = {
-        "epoch": 20,
-        "pop_size": 50,
-        "n_elites": 16,
-        "n_others": 4,
-        "patch_size": 5.0,
-        "patch_reduction": 0.985,
-        "n_sites": 3,
-        "n_elite_sites": 1,
-    }
-    paras_acor = {
-        "epoch": 20,
-        "pop_size": 50,
-        "sample_count": 25,
-        "intent_factor": 0.5,
-        "zeta": 1.0,
-    }
-    paras_alo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_ao = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_ba = {
-        "epoch": 20,
-        "pop_size": 50,
-        "loudness": 0.8,
-        "pulse_rate": 0.95,
-        "pf_min": 0.,
-        "pf_max": 10.,
-    }
-    paras_adaptive_ba = {
-        "epoch": 20,
-        "pop_size": 50,
-        "loudness_min": 1.0,
-        "loudness_max": 2.0,
-        "pr_min": 0.15,
-        "pr_max": 0.85,
-        "pf_min": 0.,
-        "pf_max": 10.,
-    }
-    paras_dev_ba = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pulse_rate": 0.95,
-        "pf_min": 0.,
-        "pf_max": 10.,
-    }
-    paras_beesa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "selected_site_ratio": 0.5,
-        "elite_site_ratio": 0.4,
-        "selected_site_bee_ratio": 0.1,
-        "elite_site_bee_ratio": 2.0,
-        "dance_radius": 0.1,
-        "dance_reduction": 0.99,
-    }
-    paras_prob_beesa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "recruited_bee_ratio": 0.1,
-        "dance_radius": 0.1,
-        "dance_reduction": 0.99,
-    }
-    paras_bes = {
-        "epoch": 20,
-        "pop_size": 50,
-        "a_factor": 10,
-        "R_factor": 1.5,
-        "alpha": 2.0,
-        "c1": 2.0,
-        "c2": 2.0,
-    }
-    paras_bfo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "Ci": 0.01,
-        "Ped": 0.25,
-        "Nc": 5,
-        "Ns": 4,
-        "d_attract": 0.1,
-        "w_attract": 0.2,
-        "h_repels": 0.1,
-        "w_repels": 10,
-    }
-    paras_abfo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "C_s": 0.1,
-        "C_e": 0.001,
-        "Ped": 0.01,
-        "Ns": 4,
-        "N_adapt": 4,
-        "N_split": 40,
-    }
-    paras_bsa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "ff": 10,
-        "pff": 0.8,
-        "c1": 1.5,
-        "c2": 1.5,
-        "a1": 1.0,
-        "a2": 1.0,
-        "fl": 0.5,
-    }
-    paras_coa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "n_coyotes": 5,
-    }
-    paras_csa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "p_a": 0.3,
-    }
-    paras_cso = {
-        "epoch": 20,
-        "pop_size": 50,
-        "mixture_ratio": 0.15,
-        "smp": 5,
-        "spc": False,
-        "cdc": 0.8,
-        "srd": 0.15,
-        "c1": 0.4,
-        "w_min": 0.4,
-        "w_max": 0.9,
-        "selected_strategy": 1,
-    }
-    paras_do = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_eho = {
-        "epoch": 20,
-        "pop_size": 50,
-        "alpha": 0.5,
-        "beta": 0.5,
-        "n_clans": 5,
-    }
-    paras_fa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "max_sparks": 20,
-        "p_a": 0.04,
-        "p_b": 0.8,
-        "max_ea": 40,
-        "m_sparks": 5,
-    }
-    paras_ffa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "gamma": 0.001,
-        "beta_base": 2,
-        "alpha": 0.2,
-        "alpha_damp": 0.99,
-        "delta": 0.05,
-        "exponent": 2,
-    }
-    paras_foa = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_goa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "c_min": 0.00004,
-        "c_max": 1.0,
-    }
-    paras_gwo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_hgs = {
-        "epoch": 20,
-        "pop_size": 50,
-        "PUP": 0.08,
-        "LH": 10000,
-    }
-    paras_hho = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_ja = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_mfo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_mrfo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "somersault_range": 2.0,
-    }
-    paras_msa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "n_best": 5,
-        "partition": 0.5,
-        "max_step_size": 1.0,
-    }
-    paras_nmra = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pb": 0.75,
-    }
-    paras_improved_nmra = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pb": 0.75,
-        "pm": 0.01,
-    }
-    paras_pfa = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_pso = {
-        "epoch": 20,
-        "pop_size": 50,
-        "c1": 2.05,
-        "c2": 2.05,
-        "w_min": 0.4,
-        "w_max": 0.9,
-    }
-    paras_ppso = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_hpso_tvac = {
-        "epoch": 20,
-        "pop_size": 50,
-        "ci": 0.5,
-        "cf": 0.0,
-    }
-    paras_cpso = {
-        "epoch": 20,
-        "pop_size": 50,
-        "c1": 2.05,
-        "c2": 2.05,
-        "w_min": 0.4,
-        "w_max": 0.9,
-    }
-    paras_clpso = {
-        "epoch": 20,
-        "pop_size": 50,
-        "c_local": 1.2,
-        "w_min": 0.4,
-        "w_max": 0.9,
-        "max_flag": 7,
-    }
-    paras_sfo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pp": 0.1,
-        "AP": 4.0,
-        "epsilon": 0.0001,
-    }
-    paras_improved_sfo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "pp": 0.1,
-    }
-    paras_sho = {
-        "epoch": 20,
-        "pop_size": 50,
-        "h_factor": 5.0,
-        "N_tried": 10,
-    }
-    paras_slo = paras_modified_slo = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_improved_slo = {
-        "epoch": 20,
-        "pop_size": 50,
-        "c1": 1.2,
-        "c2": 1.2
-    }
-    paras_srsr = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_ssa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "ST": 0.8,
-        "PD": 0.2,
-        "SD": 0.1,
-    }
-    paras_sso = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_sspidera = {
-        "epoch": 20,
-        "pop_size": 50,
-        "r_a": 1.0,
-        "p_c": 0.7,
-        "p_m": 0.1
-    }
-    paras_sspidero = {
-        "epoch": 20,
-        "pop_size": 50,
-        "fp_min": 0.65,
-        "fp_max": 0.9
-    }
-    paras_woa = {
-        "epoch": 20,
-        "pop_size": 50,
-    }
-    paras_hi_woa = {
-        "epoch": 20,
-        "pop_size": 50,
-        "feedback_max": 10
-    }
-
-    if __name__ == "__main__":
-            model = BBO.DevBBO(**paras_bbo)
-            model = BBO.OriginalBBO(**paras_bbo)
-            model = EOA.OriginalEOA(**paras_eoa)
-            model = IWO.OriginalIWO(**paras_eoa)
-            model = SBO.DevSBO(**paras_sbo)
-            model = SBO.OriginalSBO(**paras_sbo)
-            model = SMA.DevSMA(**paras_sma)
-            model = SMA.OriginalSMA(**paras_sma)
-            model = VCS.DevVCS(**paras_vcs)
-            model = VCS.OriginalVCS(**paras_vcs)
-            model = WHO.OriginalWHO(**paras_vcs)
-
-            model = CRO.OriginalCRO(**paras_cro)
-            model = CRO.OCRO(**paras_ocro)
-            # model = DE.BaseDE(**paras_de)
-            model = DE.JADE(**paras_jade)
-            model = DE.SADE(**paras_sade)
-            model = SHADE.OriginalSHADE(**paras_shade)
-            model = SHADE.L_SHADE(**paras_lshade)
-            model = DE.SAP_DE(**paras_sap_de)
-            model = EP.OriginalEP(**paras_ep)
-            model = EP.LevyEP(**paras_levy_ep)
-            model = ES.OriginalES(**paras_ep)
-            model = ES.LevyES(**paras_levy_ep)
-            model = FPA.OriginalFPA(**paras_fpa)
-            model = GA.BaseGA(**paras_ga)
-            model = GA.SingleGA(**paras_single_ga)
-            model = GA.MultiGA(**paras_multi_ga)
-            model = MA.OriginalMA(**paras_ma)
-
-            model = BRO.DevBRO(**paras_bro)
-            model = BRO.OriginalBRO(**paras_bro)
-            model = BSO.OriginalBSO(**paras_bso)
-            model = BSO.ImprovedBSO(**paras_improved_bso)
-            model = CA.OriginalCA(**paras_ca)
-            model = CHIO.DevCHIO(**paras_chio)
-            model = CHIO.OriginalCHIO(**paras_chio)
-            model = FBIO.DevFBIO(**paras_fbio)
-            model = FBIO.OriginalFBIO(**paras_fbio)
-            model = GSKA.DevGSKA(**paras_base_gska)
-            model = GSKA.OriginalGSKA(**paras_gska)
-            model = ICA.OriginalICA(**paras_ica)
-            model = LCO.DevLCO(**paras_lco)
-            model = LCO.OriginalLCO(**paras_lco)
-            model = LCO.ImprovedLCO(**paras_improved_lco)
-            model = QSA.DevQSA(**paras_qsa)
-            model = QSA.OriginalQSA(**paras_qsa)
-            model = QSA.OppoQSA(**paras_qsa)
-            model = QSA.LevyQSA(**paras_qsa)
-            model = QSA.ImprovedQSA(**paras_qsa)
-            model = SARO.DevSARO(**paras_saro)
-            model = SARO.OriginalSARO(**paras_saro)
-            model = SSDO.OriginalSSDO(**paras_ssdo)
-            model = TLO.DevTLO(**paras_tlo)
-            model = TLO.OriginalTLO(**paras_tlo)
-            model = TLO.ImprovedTLO(**paras_improved_tlo)
-
-            model = AOA.OriginalAOA(**paras_aoa)
-            model = CEM.OriginalCEM(**paras_cem)
-            model = CGO.OriginalCGO(**paras_cgo)
-            model = GBO.OriginalGBO(**paras_gbo)
-            model = HC.OriginalHC(**paras_hc)
-            model = HC.SwarmHC(**paras_swarm_hc)
-            model = PSS.OriginalPSS(**paras_pss)
-            model = SCA.OriginalSCA(**paras_sca)
-            model = SCA.DevSCA(**paras_sca)
-
-            model = HS.DevHS(**paras_hs)
-            model = HS.OriginalHS(**paras_hs)
-
-            model = AEO.OriginalAEO(**paras_aeo)
-            model = AEO.EnhancedAEO(**paras_aeo)
-            model = AEO.ModifiedAEO(**paras_aeo)
-            model = AEO.ImprovedAEO(**paras_aeo)
-            model = AEO.AugmentedAEO(**paras_aeo)
-            model = GCO.DevGCO(**paras_aeo)
-            model = GCO.OriginalGCO(**paras_aeo)
-            model = WCA.OriginalWCA(**paras_wca)
-
-            model = ArchOA.OriginalArchOA(**paras_archoa)
-            model = ASO.OriginalASO(**paras_aso)
-            model = EFO.OriginalEFO(**paras_efo)
-            model = EFO.DevEFO(**paras_efo)
-            model = EO.OriginalEO(**paras_eo)
-            model = EO.AdaptiveEO(**paras_eo)
-            model = EO.ModifiedEO(**paras_eo)
-            model = HGSO.OriginalHGSO(**paras_hgso)
-            model = MVO.OriginalMVO(**paras_mvo)
-            model = NRO.OriginalNRO(**paras_nro)
-            model = SA.OriginalSA(**paras_sa)
-            model = SA.SwarmSA(**paras_sa)
-            model = SA.GaussianSA(**paras_sa)
-            model = TWO.OriginalTWO(**paras_two)
-            model = TWO.OppoTWO(**paras_two)
-            model = TWO.LevyTWO(**paras_two)
-            model = TWO.EnhancedTWO(**paras_two)
-            model = WDO.OriginalWDO(**paras_wdo)
-
-            model = ABC.OriginalABC(**paras_abc)
-            model = ACOR.OriginalACOR(**paras_acor)
-            model = ALO.OriginalALO(**paras_alo)
-            model = AO.OriginalAO(**paras_ao)
-            model = ALO.DevALO(**paras_alo)
-            model = BA.OriginalBA(**paras_ba)
-            model = BA.AdaptiveBA(**paras_adaptive_ba)
-            model = BA.DevBA(**paras_dev_ba)
-            model = BeesA.OriginalBeesA(**paras_beesa)
-            model = BeesA.ProbBeesA(**paras_prob_beesa)
-            model = BES.OriginalBES(**paras_bes)
-            model = BFO.OriginalBFO(**paras_bfo)
-            model = BFO.ABFO(**paras_abfo)
-            model = BSA.OriginalBSA(**paras_bsa)
-            model = COA.OriginalCOA(**paras_coa)
-            model = CSA.OriginalCSA(**paras_csa)
-            model = CSO.OriginalCSO(**paras_cso)
-            model = DO.OriginalDO(**paras_do)
-            model = EHO.OriginalEHO(**paras_eho)
-            model = FA.OriginalFA(**paras_fa)
-            model = FFA.OriginalFFA(**paras_ffa)
-            model = FOA.OriginalFOA(**paras_foa)
-            model = FOA.DevFOA(**paras_foa)
-            model = FOA.WhaleFOA(**paras_foa)
-            model = GOA.OriginalGOA(**paras_goa)
-            model = GWO.OriginalGWO(**paras_gwo)
-            model = GWO.RW_GWO(**paras_gwo)
-            model = HGS.OriginalHGS(**paras_hgs)
-            model = HHO.OriginalHHO(**paras_hho)
-            model = JA.OriginalJA(**paras_ja)
-            model = JA.DevJA(**paras_ja)
-            model = JA.LevyJA(**paras_ja)
-            model = MFO.OriginalMFO(**paras_mfo)
-            # model = MFO.BaseMFO(**paras_mfo)
-            model = MRFO.OriginalMRFO(**paras_mrfo)
-            model = MSA.OriginalMSA(**paras_msa)
-            model = NMRA.ImprovedNMRA(**paras_improved_nmra)
-            model = NMRA.OriginalNMRA(**paras_nmra)
-            model = PFA.OriginalPFA(**paras_pfa)
-            model = PSO.OriginalPSO(**paras_pso)
-            model = PSO.P_PSO(**paras_ppso)
-            model = PSO.HPSO_TVAC(**paras_hpso_tvac)
-            model = PSO.C_PSO(**paras_cpso)
-            model = PSO.CL_PSO(**paras_clpso)
-            model = SFO.OriginalSFO(**paras_sfo)
-            model = SFO.ImprovedSFO(**paras_improved_sfo)
-            model = SHO.OriginalSHO(**paras_sho)
-            model = SLO.OriginalSLO(**paras_slo)
-            model = SLO.ModifiedSLO(**paras_modified_slo)
-            model = SLO.ImprovedSLO(**paras_improved_slo)
-            model = SRSR.OriginalSRSR(**paras_srsr)
-            model = SSA.OriginalSSA(**paras_ssa)
-            model = SSA.DevSSA(**paras_ssa)
-            model = SSO.OriginalSSO(**paras_sso)
-            model = SSpiderA.OriginalSSpiderA(**paras_sspidera)
-            model = SSpiderO.OriginalSSpiderO(**paras_sspidero)
-            model = WOA.OriginalWOA(**paras_woa)
-            model = WOA.HI_WOA(**paras_hi_woa)
-
-            g_best = model.solve(problem)
-            print(model.get_parameters())
-            print(model.get_name())
-            print(model.problem.get_name())
-            print(model.get_attributes()["g_best"])
+        from mealpy import BBO, PSO, GA, ALO, AO, ARO, AVOA, BA, BBOA, BMO, EOA, IWO
+        from mealpy import SBO, SMA, SOA, SOS, TPO, TSA, VCS, WHO, AOA, CEM, CGO, CircleSA, GBO, HC, INFO, PSS, RUN, SCA
+        from mealpy import SHIO, TS, HS, AEO, GCO, WCA, CRO, DE, EP, ES, FPA, MA, SHADE, BRO, BSO, CA, CHIO, FBIO, GSKA, HBO
+        from mealpy import HCO, ICA, LCO, WarSO, TOA, TLO, SSDO, SPBO, SARO, QSA, ArchOA, ASO, CDO, EFO, EO, EVO, FLA
+        from mealpy import HGSO, MVO, NRO, RIME, SA, WDO, TWO, ABC, ACOR, AGTO, BeesA, BES, BFO, ZOA, WOA, WaOA, TSO
+        from mealpy import TDO, STO, SSpiderO, SSpiderA, SSO, SSA, SRSR, SLO, SHO, SFO, ServalOA, SeaHO, SCSO, POA
+        from mealpy import PFA, OOA, NGO, NMRA, MSA, MRFO, MPA, MGO, MFO, JA, HHO, HGS, HBA, GWO, GTO, GOA
+        from mealpy import GJO, FOX, FOA, FFO, FFA, FA, ESOA, EHO, DO, DMOA, CSO, CSA, CoatiOA, COA, BSA
+        from mealpy import StringVar, FloatVar, BoolVar, PermutationVar, MixedSetVar, IntegerVar, BinaryVar
+        from mealpy import Tuner, Multitask, Problem, Optimizer, Termination, ParameterGrid
+        from mealpy import get_all_optimizers, get_optimizer_by_name
+        import numpy as np
+    
+        def objective_function(solution):
+            return np.sum(solution ** 2)
+    
+        problem = {
+            "obj_func": objective_function,
+            "bounds": FloatVar(lb=[-3] * 20, ub=[5] * 20),
+            "name": "Squared Problem",
+            "log_to": "file",
+            "log_file": "results.log"
+        }
+    
+        paras_bbo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "p_m": 0.01,
+            "elites": 2,
+        }
+        paras_eoa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "p_c": 0.9,
+            "p_m": 0.01,
+            "n_best": 2,
+            "alpha": 0.98,
+            "beta": 0.9,
+            "gamma": 0.9,
+        }
+        paras_iwo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "seed_min": 3,
+            "seed_max": 9,
+            "exponent": 3,
+            "sigma_start": 0.6,
+            "sigma_end": 0.01,
+        }
+        paras_sbo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "alpha": 0.9,
+            "p_m": 0.05,
+            "psw": 0.02,
+        }
+        paras_sma = {
+            "epoch": 20,
+            "pop_size": 50,
+            "p_t": 0.03,
+        }
+        paras_vcs = {
+            "epoch": 20,
+            "pop_size": 50,
+            "lamda": 0.5,
+            "sigma": 0.3,
+        }
+        paras_who = {
+            "epoch": 20,
+            "pop_size": 50,
+            "n_explore_step": 3,
+            "n_exploit_step": 3,
+            "eta": 0.15,
+            "p_hi": 0.9,
+            "local_alpha": 0.9,
+            "local_beta": 0.3,
+            "global_alpha": 0.2,
+            "global_beta": 0.8,
+            "delta_w": 2.0,
+            "delta_c": 2.0,
+        }
+        paras_cro = {
+            "epoch": 20,
+            "pop_size": 50,
+            "po": 0.4,
+            "Fb": 0.9,
+            "Fa": 0.1,
+            "Fd": 0.1,
+            "Pd": 0.5,
+            "GCR": 0.1,
+            "gamma_min": 0.02,
+            "gamma_max": 0.2,
+            "n_trials": 5,
+        }
+        paras_ocro = dict(paras_cro)
+        paras_ocro["restart_count"] = 5
+    
+        paras_de = {
+            "epoch": 20,
+            "pop_size": 50,
+            "wf": 0.7,
+            "cr": 0.9,
+            "strategy": 0,
+        }
+        paras_jade = {
+            "epoch": 20,
+            "pop_size": 50,
+            "miu_f": 0.5,
+            "miu_cr": 0.5,
+            "pt": 0.1,
+            "ap": 0.1,
+        }
+        paras_sade = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_shade = paras_lshade = {
+            "epoch": 20,
+            "pop_size": 50,
+            "miu_f": 0.5,
+            "miu_cr": 0.5,
+        }
+        paras_sap_de = {
+            "epoch": 20,
+            "pop_size": 50,
+            "branch": "ABS"
+        }
+        paras_ep = paras_levy_ep = {
+            "epoch": 20,
+            "pop_size": 50,
+            "bout_size": 0.05
+        }
+        paras_es = paras_levy_es = {
+            "epoch": 20,
+            "pop_size": 50,
+            "lamda": 0.75
+        }
+        paras_fpa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "p_s": 0.8,
+            "levy_multiplier": 0.2
+        }
+        paras_ga = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pc": 0.9,
+            "pm": 0.05,
+        }
+        paras_single_ga = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pc": 0.9,
+            "pm": 0.8,
+            "selection": "roulette",
+            "crossover": "uniform",
+            "mutation": "swap",
+        }
+        paras_multi_ga = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pc": 0.9,
+            "pm": 0.05,
+            "selection": "roulette",
+            "crossover": "uniform",
+            "mutation": "swap",
+        }
+        paras_ma = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pc": 0.85,
+            "pm": 0.15,
+            "p_local": 0.5,
+            "max_local_gens": 10,
+            "bits_per_param": 4,
+        }
+    
+        paras_bro = {
+            "epoch": 20,
+            "pop_size": 50,
+            "threshold": 3,
+        }
+        paras_improved_bso = {
+            "epoch": 20,
+            "pop_size": 50,
+            "m_clusters": 5,
+            "p1": 0.2,
+            "p2": 0.8,
+            "p3": 0.4,
+            "p4": 0.5,
+        }
+        paras_bso = dict(paras_improved_bso)
+        paras_bso["slope"] = 20
+        paras_ca = {
+            "epoch": 20,
+            "pop_size": 50,
+            "accepted_rate": 0.15,
+        }
+        paras_chio = {
+            "epoch": 20,
+            "pop_size": 50,
+            "brr": 0.15,
+            "max_age": 3
+        }
+        paras_fbio = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_base_gska = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pb": 0.1,
+            "kr": 0.9,
+        }
+        paras_gska = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pb": 0.1,
+            "kf": 0.5,
+            "kr": 0.9,
+            "kg": 5,
+        }
+        paras_ica = {
+            "epoch": 20,
+            "pop_size": 50,
+            "empire_count": 5,
+            "assimilation_coeff": 1.5,
+            "revolution_prob": 0.05,
+            "revolution_rate": 0.1,
+            "revolution_step_size": 0.1,
+            "zeta": 0.1,
+        }
+        paras_lco = {
+            "epoch": 20,
+            "pop_size": 50,
+            "r1": 2.35,
+        }
+        paras_improved_lco = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_qsa = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_saro = {
+            "epoch": 20,
+            "pop_size": 50,
+            "se": 0.5,
+            "mu": 15
+        }
+        paras_ssdo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_tlo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_improved_tlo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "n_teachers": 5,
+        }
+    
+        paras_aoa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "alpha": 5,
+            "miu": 0.5,
+            "moa_min": 0.2,
+            "moa_max": 0.9,
+        }
+        paras_cem = {
+            "epoch": 20,
+            "pop_size": 50,
+            "n_best": 20,
+            "alpha": 0.7,
+        }
+        paras_cgo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_gbo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pr": 0.5,
+            "beta_min": 0.2,
+            "beta_max": 1.2,
+        }
+        paras_hc = {
+            "epoch": 20,
+            "pop_size": 50,
+            "neighbour_size": 50
+        }
+        paras_swarm_hc = {
+            "epoch": 20,
+            "pop_size": 50,
+            "neighbour_size": 10
+        }
+        paras_pss = {
+            "epoch": 20,
+            "pop_size": 50,
+            "acceptance_rate": 0.8,
+            "sampling_method": "LHS",
+        }
+        paras_sca = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+    
+        paras_hs = {
+            "epoch": 20,
+            "pop_size": 50,
+            "c_r": 0.95,
+            "pa_r": 0.05
+        }
+    
+        paras_aeo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_gco = {
+            "epoch": 20,
+            "pop_size": 50,
+            "cr": 0.7,
+            "wf": 1.25,
+        }
+        paras_wca = {
+            "epoch": 20,
+            "pop_size": 50,
+            "nsr": 4,
+            "wc": 2.0,
+            "dmax": 1e-6
+        }
+    
+        paras_archoa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "c1": 2,
+            "c2": 5,
+            "c3": 2,
+            "c4": 0.5,
+            "acc_max": 0.9,
+            "acc_min": 0.1,
+        }
+        paras_aso = {
+            "epoch": 20,
+            "pop_size": 50,
+            "alpha": 50,
+            "beta": 0.2,
+        }
+        paras_efo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "r_rate": 0.3,
+            "ps_rate": 0.85,
+            "p_field": 0.1,
+            "n_field": 0.45,
+        }
+        paras_eo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_hgso = {
+            "epoch": 20,
+            "pop_size": 50,
+            "n_clusters": 3,
+        }
+        paras_mvo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "wep_min": 0.2,
+            "wep_max": 1.0,
+        }
+        paras_nro = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_sa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "max_sub_iter": 5,
+            "t0": 1000,
+            "t1": 1,
+            "move_count": 5,
+            "mutation_rate": 0.1,
+            "mutation_step_size": 0.1,
+            "mutation_step_size_damp": 0.99,
+        }
+        paras_two = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_wdo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "RT": 3,
+            "g_c": 0.2,
+            "alp": 0.4,
+            "c_e": 0.4,
+            "max_v": 0.3,
+        }
+    
+        paras_abc = {
+            "epoch": 20,
+            "pop_size": 50,
+            "n_elites": 16,
+            "n_others": 4,
+            "patch_size": 5.0,
+            "patch_reduction": 0.985,
+            "n_sites": 3,
+            "n_elite_sites": 1,
+        }
+        paras_acor = {
+            "epoch": 20,
+            "pop_size": 50,
+            "sample_count": 25,
+            "intent_factor": 0.5,
+            "zeta": 1.0,
+        }
+        paras_alo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_ao = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_ba = {
+            "epoch": 20,
+            "pop_size": 50,
+            "loudness": 0.8,
+            "pulse_rate": 0.95,
+            "pf_min": 0.,
+            "pf_max": 10.,
+        }
+        paras_adaptive_ba = {
+            "epoch": 20,
+            "pop_size": 50,
+            "loudness_min": 1.0,
+            "loudness_max": 2.0,
+            "pr_min": 0.15,
+            "pr_max": 0.85,
+            "pf_min": 0.,
+            "pf_max": 10.,
+        }
+        paras_dev_ba = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pulse_rate": 0.95,
+            "pf_min": 0.,
+            "pf_max": 10.,
+        }
+        paras_beesa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "selected_site_ratio": 0.5,
+            "elite_site_ratio": 0.4,
+            "selected_site_bee_ratio": 0.1,
+            "elite_site_bee_ratio": 2.0,
+            "dance_radius": 0.1,
+            "dance_reduction": 0.99,
+        }
+        paras_prob_beesa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "recruited_bee_ratio": 0.1,
+            "dance_radius": 0.1,
+            "dance_reduction": 0.99,
+        }
+        paras_bes = {
+            "epoch": 20,
+            "pop_size": 50,
+            "a_factor": 10,
+            "R_factor": 1.5,
+            "alpha": 2.0,
+            "c1": 2.0,
+            "c2": 2.0,
+        }
+        paras_bfo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "Ci": 0.01,
+            "Ped": 0.25,
+            "Nc": 5,
+            "Ns": 4,
+            "d_attract": 0.1,
+            "w_attract": 0.2,
+            "h_repels": 0.1,
+            "w_repels": 10,
+        }
+        paras_abfo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "C_s": 0.1,
+            "C_e": 0.001,
+            "Ped": 0.01,
+            "Ns": 4,
+            "N_adapt": 4,
+            "N_split": 40,
+        }
+        paras_bsa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "ff": 10,
+            "pff": 0.8,
+            "c1": 1.5,
+            "c2": 1.5,
+            "a1": 1.0,
+            "a2": 1.0,
+            "fl": 0.5,
+        }
+        paras_coa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "n_coyotes": 5,
+        }
+        paras_csa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "p_a": 0.3,
+        }
+        paras_cso = {
+            "epoch": 20,
+            "pop_size": 50,
+            "mixture_ratio": 0.15,
+            "smp": 5,
+            "spc": False,
+            "cdc": 0.8,
+            "srd": 0.15,
+            "c1": 0.4,
+            "w_min": 0.4,
+            "w_max": 0.9,
+            "selected_strategy": 1,
+        }
+        paras_do = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_eho = {
+            "epoch": 20,
+            "pop_size": 50,
+            "alpha": 0.5,
+            "beta": 0.5,
+            "n_clans": 5,
+        }
+        paras_fa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "max_sparks": 20,
+            "p_a": 0.04,
+            "p_b": 0.8,
+            "max_ea": 40,
+            "m_sparks": 5,
+        }
+        paras_ffa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "gamma": 0.001,
+            "beta_base": 2,
+            "alpha": 0.2,
+            "alpha_damp": 0.99,
+            "delta": 0.05,
+            "exponent": 2,
+        }
+        paras_foa = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_goa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "c_min": 0.00004,
+            "c_max": 1.0,
+        }
+        paras_gwo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_hgs = {
+            "epoch": 20,
+            "pop_size": 50,
+            "PUP": 0.08,
+            "LH": 10000,
+        }
+        paras_hho = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_ja = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_mfo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_mrfo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "somersault_range": 2.0,
+        }
+        paras_msa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "n_best": 5,
+            "partition": 0.5,
+            "max_step_size": 1.0,
+        }
+        paras_nmra = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pb": 0.75,
+        }
+        paras_improved_nmra = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pb": 0.75,
+            "pm": 0.01,
+        }
+        paras_pfa = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_pso = {
+            "epoch": 20,
+            "pop_size": 50,
+            "c1": 2.05,
+            "c2": 2.05,
+            "w_min": 0.4,
+            "w_max": 0.9,
+        }
+        paras_ppso = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_hpso_tvac = {
+            "epoch": 20,
+            "pop_size": 50,
+            "ci": 0.5,
+            "cf": 0.0,
+        }
+        paras_cpso = {
+            "epoch": 20,
+            "pop_size": 50,
+            "c1": 2.05,
+            "c2": 2.05,
+            "w_min": 0.4,
+            "w_max": 0.9,
+        }
+        paras_clpso = {
+            "epoch": 20,
+            "pop_size": 50,
+            "c_local": 1.2,
+            "w_min": 0.4,
+            "w_max": 0.9,
+            "max_flag": 7,
+        }
+        paras_sfo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pp": 0.1,
+            "AP": 4.0,
+            "epsilon": 0.0001,
+        }
+        paras_improved_sfo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "pp": 0.1,
+        }
+        paras_sho = {
+            "epoch": 20,
+            "pop_size": 50,
+            "h_factor": 5.0,
+            "N_tried": 10,
+        }
+        paras_slo = paras_modified_slo = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_improved_slo = {
+            "epoch": 20,
+            "pop_size": 50,
+            "c1": 1.2,
+            "c2": 1.2
+        }
+        paras_srsr = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_ssa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "ST": 0.8,
+            "PD": 0.2,
+            "SD": 0.1,
+        }
+        paras_sso = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_sspidera = {
+            "epoch": 20,
+            "pop_size": 50,
+            "r_a": 1.0,
+            "p_c": 0.7,
+            "p_m": 0.1
+        }
+        paras_sspidero = {
+            "epoch": 20,
+            "pop_size": 50,
+            "fp_min": 0.65,
+            "fp_max": 0.9
+        }
+        paras_woa = {
+            "epoch": 20,
+            "pop_size": 50,
+        }
+        paras_hi_woa = {
+            "epoch": 20,
+            "pop_size": 50,
+            "feedback_max": 10
+        }
+    
+        if __name__ == "__main__":
+                model = BBO.DevBBO(**paras_bbo)
+                model = BBO.OriginalBBO(**paras_bbo)
+                model = EOA.OriginalEOA(**paras_eoa)
+                model = IWO.OriginalIWO(**paras_eoa)
+                model = SBO.DevSBO(**paras_sbo)
+                model = SBO.OriginalSBO(**paras_sbo)
+                model = SMA.DevSMA(**paras_sma)
+                model = SMA.OriginalSMA(**paras_sma)
+                model = VCS.DevVCS(**paras_vcs)
+                model = VCS.OriginalVCS(**paras_vcs)
+                model = WHO.OriginalWHO(**paras_vcs)
+    
+                model = CRO.OriginalCRO(**paras_cro)
+                model = CRO.OCRO(**paras_ocro)
+                # model = DE.BaseDE(**paras_de)
+                model = DE.JADE(**paras_jade)
+                model = DE.SADE(**paras_sade)
+                model = SHADE.OriginalSHADE(**paras_shade)
+                model = SHADE.L_SHADE(**paras_lshade)
+                model = DE.SAP_DE(**paras_sap_de)
+                model = EP.OriginalEP(**paras_ep)
+                model = EP.LevyEP(**paras_levy_ep)
+                model = ES.OriginalES(**paras_ep)
+                model = ES.LevyES(**paras_levy_ep)
+                model = FPA.OriginalFPA(**paras_fpa)
+                model = GA.BaseGA(**paras_ga)
+                model = GA.SingleGA(**paras_single_ga)
+                model = GA.MultiGA(**paras_multi_ga)
+                model = MA.OriginalMA(**paras_ma)
+    
+                model = BRO.DevBRO(**paras_bro)
+                model = BRO.OriginalBRO(**paras_bro)
+                model = BSO.OriginalBSO(**paras_bso)
+                model = BSO.ImprovedBSO(**paras_improved_bso)
+                model = CA.OriginalCA(**paras_ca)
+                model = CHIO.DevCHIO(**paras_chio)
+                model = CHIO.OriginalCHIO(**paras_chio)
+                model = FBIO.DevFBIO(**paras_fbio)
+                model = FBIO.OriginalFBIO(**paras_fbio)
+                model = GSKA.DevGSKA(**paras_base_gska)
+                model = GSKA.OriginalGSKA(**paras_gska)
+                model = ICA.OriginalICA(**paras_ica)
+                model = LCO.DevLCO(**paras_lco)
+                model = LCO.OriginalLCO(**paras_lco)
+                model = LCO.ImprovedLCO(**paras_improved_lco)
+                model = QSA.DevQSA(**paras_qsa)
+                model = QSA.OriginalQSA(**paras_qsa)
+                model = QSA.OppoQSA(**paras_qsa)
+                model = QSA.LevyQSA(**paras_qsa)
+                model = QSA.ImprovedQSA(**paras_qsa)
+                model = SARO.DevSARO(**paras_saro)
+                model = SARO.OriginalSARO(**paras_saro)
+                model = SSDO.OriginalSSDO(**paras_ssdo)
+                model = TLO.DevTLO(**paras_tlo)
+                model = TLO.OriginalTLO(**paras_tlo)
+                model = TLO.ImprovedTLO(**paras_improved_tlo)
+    
+                model = AOA.OriginalAOA(**paras_aoa)
+                model = CEM.OriginalCEM(**paras_cem)
+                model = CGO.OriginalCGO(**paras_cgo)
+                model = GBO.OriginalGBO(**paras_gbo)
+                model = HC.OriginalHC(**paras_hc)
+                model = HC.SwarmHC(**paras_swarm_hc)
+                model = PSS.OriginalPSS(**paras_pss)
+                model = SCA.OriginalSCA(**paras_sca)
+                model = SCA.DevSCA(**paras_sca)
+    
+                model = HS.DevHS(**paras_hs)
+                model = HS.OriginalHS(**paras_hs)
+    
+                model = AEO.OriginalAEO(**paras_aeo)
+                model = AEO.EnhancedAEO(**paras_aeo)
+                model = AEO.ModifiedAEO(**paras_aeo)
+                model = AEO.ImprovedAEO(**paras_aeo)
+                model = AEO.AugmentedAEO(**paras_aeo)
+                model = GCO.DevGCO(**paras_aeo)
+                model = GCO.OriginalGCO(**paras_aeo)
+                model = WCA.OriginalWCA(**paras_wca)
+    
+                model = ArchOA.OriginalArchOA(**paras_archoa)
+                model = ASO.OriginalASO(**paras_aso)
+                model = EFO.OriginalEFO(**paras_efo)
+                model = EFO.DevEFO(**paras_efo)
+                model = EO.OriginalEO(**paras_eo)
+                model = EO.AdaptiveEO(**paras_eo)
+                model = EO.ModifiedEO(**paras_eo)
+                model = HGSO.OriginalHGSO(**paras_hgso)
+                model = MVO.OriginalMVO(**paras_mvo)
+                model = NRO.OriginalNRO(**paras_nro)
+                model = SA.OriginalSA(**paras_sa)
+                model = SA.SwarmSA(**paras_sa)
+                model = SA.GaussianSA(**paras_sa)
+                model = TWO.OriginalTWO(**paras_two)
+                model = TWO.OppoTWO(**paras_two)
+                model = TWO.LevyTWO(**paras_two)
+                model = TWO.EnhancedTWO(**paras_two)
+                model = WDO.OriginalWDO(**paras_wdo)
+    
+                model = ABC.OriginalABC(**paras_abc)
+                model = ACOR.OriginalACOR(**paras_acor)
+                model = ALO.OriginalALO(**paras_alo)
+                model = AO.OriginalAO(**paras_ao)
+                model = ALO.DevALO(**paras_alo)
+                model = BA.OriginalBA(**paras_ba)
+                model = BA.AdaptiveBA(**paras_adaptive_ba)
+                model = BA.DevBA(**paras_dev_ba)
+                model = BeesA.OriginalBeesA(**paras_beesa)
+                model = BeesA.ProbBeesA(**paras_prob_beesa)
+                model = BES.OriginalBES(**paras_bes)
+                model = BFO.OriginalBFO(**paras_bfo)
+                model = BFO.ABFO(**paras_abfo)
+                model = BSA.OriginalBSA(**paras_bsa)
+                model = COA.OriginalCOA(**paras_coa)
+                model = CSA.OriginalCSA(**paras_csa)
+                model = CSO.OriginalCSO(**paras_cso)
+                model = DO.OriginalDO(**paras_do)
+                model = EHO.OriginalEHO(**paras_eho)
+                model = FA.OriginalFA(**paras_fa)
+                model = FFA.OriginalFFA(**paras_ffa)
+                model = FOA.OriginalFOA(**paras_foa)
+                model = FOA.DevFOA(**paras_foa)
+                model = FOA.WhaleFOA(**paras_foa)
+                model = GOA.OriginalGOA(**paras_goa)
+                model = GWO.OriginalGWO(**paras_gwo)
+                model = GWO.RW_GWO(**paras_gwo)
+                model = HGS.OriginalHGS(**paras_hgs)
+                model = HHO.OriginalHHO(**paras_hho)
+                model = JA.OriginalJA(**paras_ja)
+                model = JA.DevJA(**paras_ja)
+                model = JA.LevyJA(**paras_ja)
+                model = MFO.OriginalMFO(**paras_mfo)
+                # model = MFO.BaseMFO(**paras_mfo)
+                model = MRFO.OriginalMRFO(**paras_mrfo)
+                model = MSA.OriginalMSA(**paras_msa)
+                model = NMRA.ImprovedNMRA(**paras_improved_nmra)
+                model = NMRA.OriginalNMRA(**paras_nmra)
+                model = PFA.OriginalPFA(**paras_pfa)
+                model = PSO.OriginalPSO(**paras_pso)
+                model = PSO.P_PSO(**paras_ppso)
+                model = PSO.HPSO_TVAC(**paras_hpso_tvac)
+                model = PSO.C_PSO(**paras_cpso)
+                model = PSO.CL_PSO(**paras_clpso)
+                model = SFO.OriginalSFO(**paras_sfo)
+                model = SFO.ImprovedSFO(**paras_improved_sfo)
+                model = SHO.OriginalSHO(**paras_sho)
+                model = SLO.OriginalSLO(**paras_slo)
+                model = SLO.ModifiedSLO(**paras_modified_slo)
+                model = SLO.ImprovedSLO(**paras_improved_slo)
+                model = SRSR.OriginalSRSR(**paras_srsr)
+                model = SSA.OriginalSSA(**paras_ssa)
+                model = SSA.DevSSA(**paras_ssa)
+                model = SSO.OriginalSSO(**paras_sso)
+                model = SSpiderA.OriginalSSpiderA(**paras_sspidera)
+                model = SSpiderO.OriginalSSpiderO(**paras_sspidero)
+                model = WOA.OriginalWOA(**paras_woa)
+                model = WOA.HI_WOA(**paras_hi_woa)
+    
+                g_best = model.solve(problem)
+                print(model.get_parameters())
+                print(model.get_name())
+                print(model.problem.get_name())
+                print(model.get_attributes()["g_best"])
 
 
 .. toctree::

From c8e21e6c62311e6aace2ac2bac0b52ff02925bad Mon Sep 17 00:00:00 2001
From: Godot <30374962+Godot115@users.noreply.github.com>
Date: Mon, 15 Apr 2024 06:29:03 +0800
Subject: [PATCH 3/3] Update import_all_models.rst

---
 .../general/advances/import_all_models.rst    | 1776 ++++++++---------
 1 file changed, 888 insertions(+), 888 deletions(-)

diff --git a/docs/source/pages/general/advances/import_all_models.rst b/docs/source/pages/general/advances/import_all_models.rst
index 3b72131f..1c4ca60a 100644
--- a/docs/source/pages/general/advances/import_all_models.rst
+++ b/docs/source/pages/general/advances/import_all_models.rst
@@ -3,894 +3,894 @@ Import All Models
 
 .. code-block:: python
 
-        from mealpy import BBO, PSO, GA, ALO, AO, ARO, AVOA, BA, BBOA, BMO, EOA, IWO
-        from mealpy import SBO, SMA, SOA, SOS, TPO, TSA, VCS, WHO, AOA, CEM, CGO, CircleSA, GBO, HC, INFO, PSS, RUN, SCA
-        from mealpy import SHIO, TS, HS, AEO, GCO, WCA, CRO, DE, EP, ES, FPA, MA, SHADE, BRO, BSO, CA, CHIO, FBIO, GSKA, HBO
-        from mealpy import HCO, ICA, LCO, WarSO, TOA, TLO, SSDO, SPBO, SARO, QSA, ArchOA, ASO, CDO, EFO, EO, EVO, FLA
-        from mealpy import HGSO, MVO, NRO, RIME, SA, WDO, TWO, ABC, ACOR, AGTO, BeesA, BES, BFO, ZOA, WOA, WaOA, TSO
-        from mealpy import TDO, STO, SSpiderO, SSpiderA, SSO, SSA, SRSR, SLO, SHO, SFO, ServalOA, SeaHO, SCSO, POA
-        from mealpy import PFA, OOA, NGO, NMRA, MSA, MRFO, MPA, MGO, MFO, JA, HHO, HGS, HBA, GWO, GTO, GOA
-        from mealpy import GJO, FOX, FOA, FFO, FFA, FA, ESOA, EHO, DO, DMOA, CSO, CSA, CoatiOA, COA, BSA
-        from mealpy import StringVar, FloatVar, BoolVar, PermutationVar, MixedSetVar, IntegerVar, BinaryVar
-        from mealpy import Tuner, Multitask, Problem, Optimizer, Termination, ParameterGrid
-        from mealpy import get_all_optimizers, get_optimizer_by_name
-        import numpy as np
-    
-        def objective_function(solution):
-            return np.sum(solution ** 2)
-    
-        problem = {
-            "obj_func": objective_function,
-            "bounds": FloatVar(lb=[-3] * 20, ub=[5] * 20),
-            "name": "Squared Problem",
-            "log_to": "file",
-            "log_file": "results.log"
-        }
-    
-        paras_bbo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "p_m": 0.01,
-            "elites": 2,
-        }
-        paras_eoa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "p_c": 0.9,
-            "p_m": 0.01,
-            "n_best": 2,
-            "alpha": 0.98,
-            "beta": 0.9,
-            "gamma": 0.9,
-        }
-        paras_iwo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "seed_min": 3,
-            "seed_max": 9,
-            "exponent": 3,
-            "sigma_start": 0.6,
-            "sigma_end": 0.01,
-        }
-        paras_sbo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "alpha": 0.9,
-            "p_m": 0.05,
-            "psw": 0.02,
-        }
-        paras_sma = {
-            "epoch": 20,
-            "pop_size": 50,
-            "p_t": 0.03,
-        }
-        paras_vcs = {
-            "epoch": 20,
-            "pop_size": 50,
-            "lamda": 0.5,
-            "sigma": 0.3,
-        }
-        paras_who = {
-            "epoch": 20,
-            "pop_size": 50,
-            "n_explore_step": 3,
-            "n_exploit_step": 3,
-            "eta": 0.15,
-            "p_hi": 0.9,
-            "local_alpha": 0.9,
-            "local_beta": 0.3,
-            "global_alpha": 0.2,
-            "global_beta": 0.8,
-            "delta_w": 2.0,
-            "delta_c": 2.0,
-        }
-        paras_cro = {
-            "epoch": 20,
-            "pop_size": 50,
-            "po": 0.4,
-            "Fb": 0.9,
-            "Fa": 0.1,
-            "Fd": 0.1,
-            "Pd": 0.5,
-            "GCR": 0.1,
-            "gamma_min": 0.02,
-            "gamma_max": 0.2,
-            "n_trials": 5,
-        }
-        paras_ocro = dict(paras_cro)
-        paras_ocro["restart_count"] = 5
-    
-        paras_de = {
-            "epoch": 20,
-            "pop_size": 50,
-            "wf": 0.7,
-            "cr": 0.9,
-            "strategy": 0,
-        }
-        paras_jade = {
-            "epoch": 20,
-            "pop_size": 50,
-            "miu_f": 0.5,
-            "miu_cr": 0.5,
-            "pt": 0.1,
-            "ap": 0.1,
-        }
-        paras_sade = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_shade = paras_lshade = {
-            "epoch": 20,
-            "pop_size": 50,
-            "miu_f": 0.5,
-            "miu_cr": 0.5,
-        }
-        paras_sap_de = {
-            "epoch": 20,
-            "pop_size": 50,
-            "branch": "ABS"
-        }
-        paras_ep = paras_levy_ep = {
-            "epoch": 20,
-            "pop_size": 50,
-            "bout_size": 0.05
-        }
-        paras_es = paras_levy_es = {
-            "epoch": 20,
-            "pop_size": 50,
-            "lamda": 0.75
-        }
-        paras_fpa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "p_s": 0.8,
-            "levy_multiplier": 0.2
-        }
-        paras_ga = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pc": 0.9,
-            "pm": 0.05,
-        }
-        paras_single_ga = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pc": 0.9,
-            "pm": 0.8,
-            "selection": "roulette",
-            "crossover": "uniform",
-            "mutation": "swap",
-        }
-        paras_multi_ga = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pc": 0.9,
-            "pm": 0.05,
-            "selection": "roulette",
-            "crossover": "uniform",
-            "mutation": "swap",
-        }
-        paras_ma = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pc": 0.85,
-            "pm": 0.15,
-            "p_local": 0.5,
-            "max_local_gens": 10,
-            "bits_per_param": 4,
-        }
-    
-        paras_bro = {
-            "epoch": 20,
-            "pop_size": 50,
-            "threshold": 3,
-        }
-        paras_improved_bso = {
-            "epoch": 20,
-            "pop_size": 50,
-            "m_clusters": 5,
-            "p1": 0.2,
-            "p2": 0.8,
-            "p3": 0.4,
-            "p4": 0.5,
-        }
-        paras_bso = dict(paras_improved_bso)
-        paras_bso["slope"] = 20
-        paras_ca = {
-            "epoch": 20,
-            "pop_size": 50,
-            "accepted_rate": 0.15,
-        }
-        paras_chio = {
-            "epoch": 20,
-            "pop_size": 50,
-            "brr": 0.15,
-            "max_age": 3
-        }
-        paras_fbio = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_base_gska = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pb": 0.1,
-            "kr": 0.9,
-        }
-        paras_gska = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pb": 0.1,
-            "kf": 0.5,
-            "kr": 0.9,
-            "kg": 5,
-        }
-        paras_ica = {
-            "epoch": 20,
-            "pop_size": 50,
-            "empire_count": 5,
-            "assimilation_coeff": 1.5,
-            "revolution_prob": 0.05,
-            "revolution_rate": 0.1,
-            "revolution_step_size": 0.1,
-            "zeta": 0.1,
-        }
-        paras_lco = {
-            "epoch": 20,
-            "pop_size": 50,
-            "r1": 2.35,
-        }
-        paras_improved_lco = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_qsa = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_saro = {
-            "epoch": 20,
-            "pop_size": 50,
-            "se": 0.5,
-            "mu": 15
-        }
-        paras_ssdo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_tlo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_improved_tlo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "n_teachers": 5,
-        }
-    
-        paras_aoa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "alpha": 5,
-            "miu": 0.5,
-            "moa_min": 0.2,
-            "moa_max": 0.9,
-        }
-        paras_cem = {
-            "epoch": 20,
-            "pop_size": 50,
-            "n_best": 20,
-            "alpha": 0.7,
-        }
-        paras_cgo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_gbo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pr": 0.5,
-            "beta_min": 0.2,
-            "beta_max": 1.2,
-        }
-        paras_hc = {
-            "epoch": 20,
-            "pop_size": 50,
-            "neighbour_size": 50
-        }
-        paras_swarm_hc = {
-            "epoch": 20,
-            "pop_size": 50,
-            "neighbour_size": 10
-        }
-        paras_pss = {
-            "epoch": 20,
-            "pop_size": 50,
-            "acceptance_rate": 0.8,
-            "sampling_method": "LHS",
-        }
-        paras_sca = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-    
-        paras_hs = {
-            "epoch": 20,
-            "pop_size": 50,
-            "c_r": 0.95,
-            "pa_r": 0.05
-        }
-    
-        paras_aeo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_gco = {
-            "epoch": 20,
-            "pop_size": 50,
-            "cr": 0.7,
-            "wf": 1.25,
-        }
-        paras_wca = {
-            "epoch": 20,
-            "pop_size": 50,
-            "nsr": 4,
-            "wc": 2.0,
-            "dmax": 1e-6
-        }
-    
-        paras_archoa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "c1": 2,
-            "c2": 5,
-            "c3": 2,
-            "c4": 0.5,
-            "acc_max": 0.9,
-            "acc_min": 0.1,
-        }
-        paras_aso = {
-            "epoch": 20,
-            "pop_size": 50,
-            "alpha": 50,
-            "beta": 0.2,
-        }
-        paras_efo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "r_rate": 0.3,
-            "ps_rate": 0.85,
-            "p_field": 0.1,
-            "n_field": 0.45,
-        }
-        paras_eo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_hgso = {
-            "epoch": 20,
-            "pop_size": 50,
-            "n_clusters": 3,
-        }
-        paras_mvo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "wep_min": 0.2,
-            "wep_max": 1.0,
-        }
-        paras_nro = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_sa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "max_sub_iter": 5,
-            "t0": 1000,
-            "t1": 1,
-            "move_count": 5,
-            "mutation_rate": 0.1,
-            "mutation_step_size": 0.1,
-            "mutation_step_size_damp": 0.99,
-        }
-        paras_two = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_wdo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "RT": 3,
-            "g_c": 0.2,
-            "alp": 0.4,
-            "c_e": 0.4,
-            "max_v": 0.3,
-        }
-    
-        paras_abc = {
-            "epoch": 20,
-            "pop_size": 50,
-            "n_elites": 16,
-            "n_others": 4,
-            "patch_size": 5.0,
-            "patch_reduction": 0.985,
-            "n_sites": 3,
-            "n_elite_sites": 1,
-        }
-        paras_acor = {
-            "epoch": 20,
-            "pop_size": 50,
-            "sample_count": 25,
-            "intent_factor": 0.5,
-            "zeta": 1.0,
-        }
-        paras_alo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_ao = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_ba = {
-            "epoch": 20,
-            "pop_size": 50,
-            "loudness": 0.8,
-            "pulse_rate": 0.95,
-            "pf_min": 0.,
-            "pf_max": 10.,
-        }
-        paras_adaptive_ba = {
-            "epoch": 20,
-            "pop_size": 50,
-            "loudness_min": 1.0,
-            "loudness_max": 2.0,
-            "pr_min": 0.15,
-            "pr_max": 0.85,
-            "pf_min": 0.,
-            "pf_max": 10.,
-        }
-        paras_dev_ba = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pulse_rate": 0.95,
-            "pf_min": 0.,
-            "pf_max": 10.,
-        }
-        paras_beesa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "selected_site_ratio": 0.5,
-            "elite_site_ratio": 0.4,
-            "selected_site_bee_ratio": 0.1,
-            "elite_site_bee_ratio": 2.0,
-            "dance_radius": 0.1,
-            "dance_reduction": 0.99,
-        }
-        paras_prob_beesa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "recruited_bee_ratio": 0.1,
-            "dance_radius": 0.1,
-            "dance_reduction": 0.99,
-        }
-        paras_bes = {
-            "epoch": 20,
-            "pop_size": 50,
-            "a_factor": 10,
-            "R_factor": 1.5,
-            "alpha": 2.0,
-            "c1": 2.0,
-            "c2": 2.0,
-        }
-        paras_bfo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "Ci": 0.01,
-            "Ped": 0.25,
-            "Nc": 5,
-            "Ns": 4,
-            "d_attract": 0.1,
-            "w_attract": 0.2,
-            "h_repels": 0.1,
-            "w_repels": 10,
-        }
-        paras_abfo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "C_s": 0.1,
-            "C_e": 0.001,
-            "Ped": 0.01,
-            "Ns": 4,
-            "N_adapt": 4,
-            "N_split": 40,
-        }
-        paras_bsa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "ff": 10,
-            "pff": 0.8,
-            "c1": 1.5,
-            "c2": 1.5,
-            "a1": 1.0,
-            "a2": 1.0,
-            "fl": 0.5,
-        }
-        paras_coa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "n_coyotes": 5,
-        }
-        paras_csa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "p_a": 0.3,
-        }
-        paras_cso = {
-            "epoch": 20,
-            "pop_size": 50,
-            "mixture_ratio": 0.15,
-            "smp": 5,
-            "spc": False,
-            "cdc": 0.8,
-            "srd": 0.15,
-            "c1": 0.4,
-            "w_min": 0.4,
-            "w_max": 0.9,
-            "selected_strategy": 1,
-        }
-        paras_do = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_eho = {
-            "epoch": 20,
-            "pop_size": 50,
-            "alpha": 0.5,
-            "beta": 0.5,
-            "n_clans": 5,
-        }
-        paras_fa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "max_sparks": 20,
-            "p_a": 0.04,
-            "p_b": 0.8,
-            "max_ea": 40,
-            "m_sparks": 5,
-        }
-        paras_ffa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "gamma": 0.001,
-            "beta_base": 2,
-            "alpha": 0.2,
-            "alpha_damp": 0.99,
-            "delta": 0.05,
-            "exponent": 2,
-        }
-        paras_foa = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_goa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "c_min": 0.00004,
-            "c_max": 1.0,
-        }
-        paras_gwo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_hgs = {
-            "epoch": 20,
-            "pop_size": 50,
-            "PUP": 0.08,
-            "LH": 10000,
-        }
-        paras_hho = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_ja = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_mfo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_mrfo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "somersault_range": 2.0,
-        }
-        paras_msa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "n_best": 5,
-            "partition": 0.5,
-            "max_step_size": 1.0,
-        }
-        paras_nmra = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pb": 0.75,
-        }
-        paras_improved_nmra = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pb": 0.75,
-            "pm": 0.01,
-        }
-        paras_pfa = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_pso = {
-            "epoch": 20,
-            "pop_size": 50,
-            "c1": 2.05,
-            "c2": 2.05,
-            "w_min": 0.4,
-            "w_max": 0.9,
-        }
-        paras_ppso = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_hpso_tvac = {
-            "epoch": 20,
-            "pop_size": 50,
-            "ci": 0.5,
-            "cf": 0.0,
-        }
-        paras_cpso = {
-            "epoch": 20,
-            "pop_size": 50,
-            "c1": 2.05,
-            "c2": 2.05,
-            "w_min": 0.4,
-            "w_max": 0.9,
-        }
-        paras_clpso = {
-            "epoch": 20,
-            "pop_size": 50,
-            "c_local": 1.2,
-            "w_min": 0.4,
-            "w_max": 0.9,
-            "max_flag": 7,
-        }
-        paras_sfo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pp": 0.1,
-            "AP": 4.0,
-            "epsilon": 0.0001,
-        }
-        paras_improved_sfo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "pp": 0.1,
-        }
-        paras_sho = {
-            "epoch": 20,
-            "pop_size": 50,
-            "h_factor": 5.0,
-            "N_tried": 10,
-        }
-        paras_slo = paras_modified_slo = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_improved_slo = {
-            "epoch": 20,
-            "pop_size": 50,
-            "c1": 1.2,
-            "c2": 1.2
-        }
-        paras_srsr = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_ssa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "ST": 0.8,
-            "PD": 0.2,
-            "SD": 0.1,
-        }
-        paras_sso = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_sspidera = {
-            "epoch": 20,
-            "pop_size": 50,
-            "r_a": 1.0,
-            "p_c": 0.7,
-            "p_m": 0.1
-        }
-        paras_sspidero = {
-            "epoch": 20,
-            "pop_size": 50,
-            "fp_min": 0.65,
-            "fp_max": 0.9
-        }
-        paras_woa = {
-            "epoch": 20,
-            "pop_size": 50,
-        }
-        paras_hi_woa = {
-            "epoch": 20,
-            "pop_size": 50,
-            "feedback_max": 10
-        }
-    
-        if __name__ == "__main__":
-                model = BBO.DevBBO(**paras_bbo)
-                model = BBO.OriginalBBO(**paras_bbo)
-                model = EOA.OriginalEOA(**paras_eoa)
-                model = IWO.OriginalIWO(**paras_eoa)
-                model = SBO.DevSBO(**paras_sbo)
-                model = SBO.OriginalSBO(**paras_sbo)
-                model = SMA.DevSMA(**paras_sma)
-                model = SMA.OriginalSMA(**paras_sma)
-                model = VCS.DevVCS(**paras_vcs)
-                model = VCS.OriginalVCS(**paras_vcs)
-                model = WHO.OriginalWHO(**paras_vcs)
-    
-                model = CRO.OriginalCRO(**paras_cro)
-                model = CRO.OCRO(**paras_ocro)
-                # model = DE.BaseDE(**paras_de)
-                model = DE.JADE(**paras_jade)
-                model = DE.SADE(**paras_sade)
-                model = SHADE.OriginalSHADE(**paras_shade)
-                model = SHADE.L_SHADE(**paras_lshade)
-                model = DE.SAP_DE(**paras_sap_de)
-                model = EP.OriginalEP(**paras_ep)
-                model = EP.LevyEP(**paras_levy_ep)
-                model = ES.OriginalES(**paras_ep)
-                model = ES.LevyES(**paras_levy_ep)
-                model = FPA.OriginalFPA(**paras_fpa)
-                model = GA.BaseGA(**paras_ga)
-                model = GA.SingleGA(**paras_single_ga)
-                model = GA.MultiGA(**paras_multi_ga)
-                model = MA.OriginalMA(**paras_ma)
-    
-                model = BRO.DevBRO(**paras_bro)
-                model = BRO.OriginalBRO(**paras_bro)
-                model = BSO.OriginalBSO(**paras_bso)
-                model = BSO.ImprovedBSO(**paras_improved_bso)
-                model = CA.OriginalCA(**paras_ca)
-                model = CHIO.DevCHIO(**paras_chio)
-                model = CHIO.OriginalCHIO(**paras_chio)
-                model = FBIO.DevFBIO(**paras_fbio)
-                model = FBIO.OriginalFBIO(**paras_fbio)
-                model = GSKA.DevGSKA(**paras_base_gska)
-                model = GSKA.OriginalGSKA(**paras_gska)
-                model = ICA.OriginalICA(**paras_ica)
-                model = LCO.DevLCO(**paras_lco)
-                model = LCO.OriginalLCO(**paras_lco)
-                model = LCO.ImprovedLCO(**paras_improved_lco)
-                model = QSA.DevQSA(**paras_qsa)
-                model = QSA.OriginalQSA(**paras_qsa)
-                model = QSA.OppoQSA(**paras_qsa)
-                model = QSA.LevyQSA(**paras_qsa)
-                model = QSA.ImprovedQSA(**paras_qsa)
-                model = SARO.DevSARO(**paras_saro)
-                model = SARO.OriginalSARO(**paras_saro)
-                model = SSDO.OriginalSSDO(**paras_ssdo)
-                model = TLO.DevTLO(**paras_tlo)
-                model = TLO.OriginalTLO(**paras_tlo)
-                model = TLO.ImprovedTLO(**paras_improved_tlo)
-    
-                model = AOA.OriginalAOA(**paras_aoa)
-                model = CEM.OriginalCEM(**paras_cem)
-                model = CGO.OriginalCGO(**paras_cgo)
-                model = GBO.OriginalGBO(**paras_gbo)
-                model = HC.OriginalHC(**paras_hc)
-                model = HC.SwarmHC(**paras_swarm_hc)
-                model = PSS.OriginalPSS(**paras_pss)
-                model = SCA.OriginalSCA(**paras_sca)
-                model = SCA.DevSCA(**paras_sca)
-    
-                model = HS.DevHS(**paras_hs)
-                model = HS.OriginalHS(**paras_hs)
-    
-                model = AEO.OriginalAEO(**paras_aeo)
-                model = AEO.EnhancedAEO(**paras_aeo)
-                model = AEO.ModifiedAEO(**paras_aeo)
-                model = AEO.ImprovedAEO(**paras_aeo)
-                model = AEO.AugmentedAEO(**paras_aeo)
-                model = GCO.DevGCO(**paras_aeo)
-                model = GCO.OriginalGCO(**paras_aeo)
-                model = WCA.OriginalWCA(**paras_wca)
-    
-                model = ArchOA.OriginalArchOA(**paras_archoa)
-                model = ASO.OriginalASO(**paras_aso)
-                model = EFO.OriginalEFO(**paras_efo)
-                model = EFO.DevEFO(**paras_efo)
-                model = EO.OriginalEO(**paras_eo)
-                model = EO.AdaptiveEO(**paras_eo)
-                model = EO.ModifiedEO(**paras_eo)
-                model = HGSO.OriginalHGSO(**paras_hgso)
-                model = MVO.OriginalMVO(**paras_mvo)
-                model = NRO.OriginalNRO(**paras_nro)
-                model = SA.OriginalSA(**paras_sa)
-                model = SA.SwarmSA(**paras_sa)
-                model = SA.GaussianSA(**paras_sa)
-                model = TWO.OriginalTWO(**paras_two)
-                model = TWO.OppoTWO(**paras_two)
-                model = TWO.LevyTWO(**paras_two)
-                model = TWO.EnhancedTWO(**paras_two)
-                model = WDO.OriginalWDO(**paras_wdo)
-    
-                model = ABC.OriginalABC(**paras_abc)
-                model = ACOR.OriginalACOR(**paras_acor)
-                model = ALO.OriginalALO(**paras_alo)
-                model = AO.OriginalAO(**paras_ao)
-                model = ALO.DevALO(**paras_alo)
-                model = BA.OriginalBA(**paras_ba)
-                model = BA.AdaptiveBA(**paras_adaptive_ba)
-                model = BA.DevBA(**paras_dev_ba)
-                model = BeesA.OriginalBeesA(**paras_beesa)
-                model = BeesA.ProbBeesA(**paras_prob_beesa)
-                model = BES.OriginalBES(**paras_bes)
-                model = BFO.OriginalBFO(**paras_bfo)
-                model = BFO.ABFO(**paras_abfo)
-                model = BSA.OriginalBSA(**paras_bsa)
-                model = COA.OriginalCOA(**paras_coa)
-                model = CSA.OriginalCSA(**paras_csa)
-                model = CSO.OriginalCSO(**paras_cso)
-                model = DO.OriginalDO(**paras_do)
-                model = EHO.OriginalEHO(**paras_eho)
-                model = FA.OriginalFA(**paras_fa)
-                model = FFA.OriginalFFA(**paras_ffa)
-                model = FOA.OriginalFOA(**paras_foa)
-                model = FOA.DevFOA(**paras_foa)
-                model = FOA.WhaleFOA(**paras_foa)
-                model = GOA.OriginalGOA(**paras_goa)
-                model = GWO.OriginalGWO(**paras_gwo)
-                model = GWO.RW_GWO(**paras_gwo)
-                model = HGS.OriginalHGS(**paras_hgs)
-                model = HHO.OriginalHHO(**paras_hho)
-                model = JA.OriginalJA(**paras_ja)
-                model = JA.DevJA(**paras_ja)
-                model = JA.LevyJA(**paras_ja)
-                model = MFO.OriginalMFO(**paras_mfo)
-                # model = MFO.BaseMFO(**paras_mfo)
-                model = MRFO.OriginalMRFO(**paras_mrfo)
-                model = MSA.OriginalMSA(**paras_msa)
-                model = NMRA.ImprovedNMRA(**paras_improved_nmra)
-                model = NMRA.OriginalNMRA(**paras_nmra)
-                model = PFA.OriginalPFA(**paras_pfa)
-                model = PSO.OriginalPSO(**paras_pso)
-                model = PSO.P_PSO(**paras_ppso)
-                model = PSO.HPSO_TVAC(**paras_hpso_tvac)
-                model = PSO.C_PSO(**paras_cpso)
-                model = PSO.CL_PSO(**paras_clpso)
-                model = SFO.OriginalSFO(**paras_sfo)
-                model = SFO.ImprovedSFO(**paras_improved_sfo)
-                model = SHO.OriginalSHO(**paras_sho)
-                model = SLO.OriginalSLO(**paras_slo)
-                model = SLO.ModifiedSLO(**paras_modified_slo)
-                model = SLO.ImprovedSLO(**paras_improved_slo)
-                model = SRSR.OriginalSRSR(**paras_srsr)
-                model = SSA.OriginalSSA(**paras_ssa)
-                model = SSA.DevSSA(**paras_ssa)
-                model = SSO.OriginalSSO(**paras_sso)
-                model = SSpiderA.OriginalSSpiderA(**paras_sspidera)
-                model = SSpiderO.OriginalSSpiderO(**paras_sspidero)
-                model = WOA.OriginalWOA(**paras_woa)
-                model = WOA.HI_WOA(**paras_hi_woa)
-    
-                g_best = model.solve(problem)
-                print(model.get_parameters())
-                print(model.get_name())
-                print(model.problem.get_name())
-                print(model.get_attributes()["g_best"])
+	from mealpy import BBO, PSO, GA, ALO, AO, ARO, AVOA, BA, BBOA, BMO, EOA, IWO
+	from mealpy import SBO, SMA, SOA, SOS, TPO, TSA, VCS, WHO, AOA, CEM, CGO, CircleSA, GBO, HC, INFO, PSS, RUN, SCA
+	from mealpy import SHIO, TS, HS, AEO, GCO, WCA, CRO, DE, EP, ES, FPA, MA, SHADE, BRO, BSO, CA, CHIO, FBIO, GSKA, HBO
+	from mealpy import HCO, ICA, LCO, WarSO, TOA, TLO, SSDO, SPBO, SARO, QSA, ArchOA, ASO, CDO, EFO, EO, EVO, FLA
+	from mealpy import HGSO, MVO, NRO, RIME, SA, WDO, TWO, ABC, ACOR, AGTO, BeesA, BES, BFO, ZOA, WOA, WaOA, TSO
+	from mealpy import TDO, STO, SSpiderO, SSpiderA, SSO, SSA, SRSR, SLO, SHO, SFO, ServalOA, SeaHO, SCSO, POA
+	from mealpy import PFA, OOA, NGO, NMRA, MSA, MRFO, MPA, MGO, MFO, JA, HHO, HGS, HBA, GWO, GTO, GOA
+	from mealpy import GJO, FOX, FOA, FFO, FFA, FA, ESOA, EHO, DO, DMOA, CSO, CSA, CoatiOA, COA, BSA
+	from mealpy import StringVar, FloatVar, BoolVar, PermutationVar, MixedSetVar, IntegerVar, BinaryVar
+	from mealpy import Tuner, Multitask, Problem, Optimizer, Termination, ParameterGrid
+	from mealpy import get_all_optimizers, get_optimizer_by_name
+	import numpy as np
+
+	def objective_function(solution):
+	    return np.sum(solution ** 2)
+
+	problem = {
+	    "obj_func": objective_function,
+	    "bounds": FloatVar(lb=[-3] * 20, ub=[5] * 20),
+	    "name": "Squared Problem",
+	    "log_to": "file",
+	    "log_file": "results.log"
+	}
+
+	paras_bbo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "p_m": 0.01,
+	    "elites": 2,
+	}
+	paras_eoa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "p_c": 0.9,
+	    "p_m": 0.01,
+	    "n_best": 2,
+	    "alpha": 0.98,
+	    "beta": 0.9,
+	    "gamma": 0.9,
+	}
+	paras_iwo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "seed_min": 3,
+	    "seed_max": 9,
+	    "exponent": 3,
+	    "sigma_start": 0.6,
+	    "sigma_end": 0.01,
+	}
+	paras_sbo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "alpha": 0.9,
+	    "p_m": 0.05,
+	    "psw": 0.02,
+	}
+	paras_sma = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "p_t": 0.03,
+	}
+	paras_vcs = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "lamda": 0.5,
+	    "sigma": 0.3,
+	}
+	paras_who = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "n_explore_step": 3,
+	    "n_exploit_step": 3,
+	    "eta": 0.15,
+	    "p_hi": 0.9,
+	    "local_alpha": 0.9,
+	    "local_beta": 0.3,
+	    "global_alpha": 0.2,
+	    "global_beta": 0.8,
+	    "delta_w": 2.0,
+	    "delta_c": 2.0,
+	}
+	paras_cro = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "po": 0.4,
+	    "Fb": 0.9,
+	    "Fa": 0.1,
+	    "Fd": 0.1,
+	    "Pd": 0.5,
+	    "GCR": 0.1,
+	    "gamma_min": 0.02,
+	    "gamma_max": 0.2,
+	    "n_trials": 5,
+	}
+	paras_ocro = dict(paras_cro)
+	paras_ocro["restart_count"] = 5
+
+	paras_de = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "wf": 0.7,
+	    "cr": 0.9,
+	    "strategy": 0,
+	}
+	paras_jade = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "miu_f": 0.5,
+	    "miu_cr": 0.5,
+	    "pt": 0.1,
+	    "ap": 0.1,
+	}
+	paras_sade = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_shade = paras_lshade = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "miu_f": 0.5,
+	    "miu_cr": 0.5,
+	}
+	paras_sap_de = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "branch": "ABS"
+	}
+	paras_ep = paras_levy_ep = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "bout_size": 0.05
+	}
+	paras_es = paras_levy_es = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "lamda": 0.75
+	}
+	paras_fpa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "p_s": 0.8,
+	    "levy_multiplier": 0.2
+	}
+	paras_ga = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pc": 0.9,
+	    "pm": 0.05,
+	}
+	paras_single_ga = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pc": 0.9,
+	    "pm": 0.8,
+	    "selection": "roulette",
+	    "crossover": "uniform",
+	    "mutation": "swap",
+	}
+	paras_multi_ga = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pc": 0.9,
+	    "pm": 0.05,
+	    "selection": "roulette",
+	    "crossover": "uniform",
+	    "mutation": "swap",
+	}
+	paras_ma = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pc": 0.85,
+	    "pm": 0.15,
+	    "p_local": 0.5,
+	    "max_local_gens": 10,
+	    "bits_per_param": 4,
+	}
+
+	paras_bro = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "threshold": 3,
+	}
+	paras_improved_bso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "m_clusters": 5,
+	    "p1": 0.2,
+	    "p2": 0.8,
+	    "p3": 0.4,
+	    "p4": 0.5,
+	}
+	paras_bso = dict(paras_improved_bso)
+	paras_bso["slope"] = 20
+	paras_ca = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "accepted_rate": 0.15,
+	}
+	paras_chio = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "brr": 0.15,
+	    "max_age": 3
+	}
+	paras_fbio = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_base_gska = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pb": 0.1,
+	    "kr": 0.9,
+	}
+	paras_gska = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pb": 0.1,
+	    "kf": 0.5,
+	    "kr": 0.9,
+	    "kg": 5,
+	}
+	paras_ica = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "empire_count": 5,
+	    "assimilation_coeff": 1.5,
+	    "revolution_prob": 0.05,
+	    "revolution_rate": 0.1,
+	    "revolution_step_size": 0.1,
+	    "zeta": 0.1,
+	}
+	paras_lco = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "r1": 2.35,
+	}
+	paras_improved_lco = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_qsa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_saro = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "se": 0.5,
+	    "mu": 15
+	}
+	paras_ssdo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_tlo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_improved_tlo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "n_teachers": 5,
+	}
+
+	paras_aoa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "alpha": 5,
+	    "miu": 0.5,
+	    "moa_min": 0.2,
+	    "moa_max": 0.9,
+	}
+	paras_cem = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "n_best": 20,
+	    "alpha": 0.7,
+	}
+	paras_cgo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_gbo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pr": 0.5,
+	    "beta_min": 0.2,
+	    "beta_max": 1.2,
+	}
+	paras_hc = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "neighbour_size": 50
+	}
+	paras_swarm_hc = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "neighbour_size": 10
+	}
+	paras_pss = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "acceptance_rate": 0.8,
+	    "sampling_method": "LHS",
+	}
+	paras_sca = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+
+	paras_hs = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "c_r": 0.95,
+	    "pa_r": 0.05
+	}
+
+	paras_aeo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_gco = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "cr": 0.7,
+	    "wf": 1.25,
+	}
+	paras_wca = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "nsr": 4,
+	    "wc": 2.0,
+	    "dmax": 1e-6
+	}
+
+	paras_archoa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "c1": 2,
+	    "c2": 5,
+	    "c3": 2,
+	    "c4": 0.5,
+	    "acc_max": 0.9,
+	    "acc_min": 0.1,
+	}
+	paras_aso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "alpha": 50,
+	    "beta": 0.2,
+	}
+	paras_efo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "r_rate": 0.3,
+	    "ps_rate": 0.85,
+	    "p_field": 0.1,
+	    "n_field": 0.45,
+	}
+	paras_eo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_hgso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "n_clusters": 3,
+	}
+	paras_mvo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "wep_min": 0.2,
+	    "wep_max": 1.0,
+	}
+	paras_nro = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_sa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "max_sub_iter": 5,
+	    "t0": 1000,
+	    "t1": 1,
+	    "move_count": 5,
+	    "mutation_rate": 0.1,
+	    "mutation_step_size": 0.1,
+	    "mutation_step_size_damp": 0.99,
+	}
+	paras_two = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_wdo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "RT": 3,
+	    "g_c": 0.2,
+	    "alp": 0.4,
+	    "c_e": 0.4,
+	    "max_v": 0.3,
+	}
+
+	paras_abc = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "n_elites": 16,
+	    "n_others": 4,
+	    "patch_size": 5.0,
+	    "patch_reduction": 0.985,
+	    "n_sites": 3,
+	    "n_elite_sites": 1,
+	}
+	paras_acor = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "sample_count": 25,
+	    "intent_factor": 0.5,
+	    "zeta": 1.0,
+	}
+	paras_alo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_ao = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_ba = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "loudness": 0.8,
+	    "pulse_rate": 0.95,
+	    "pf_min": 0.,
+	    "pf_max": 10.,
+	}
+	paras_adaptive_ba = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "loudness_min": 1.0,
+	    "loudness_max": 2.0,
+	    "pr_min": 0.15,
+	    "pr_max": 0.85,
+	    "pf_min": 0.,
+	    "pf_max": 10.,
+	}
+	paras_dev_ba = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pulse_rate": 0.95,
+	    "pf_min": 0.,
+	    "pf_max": 10.,
+	}
+	paras_beesa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "selected_site_ratio": 0.5,
+	    "elite_site_ratio": 0.4,
+	    "selected_site_bee_ratio": 0.1,
+	    "elite_site_bee_ratio": 2.0,
+	    "dance_radius": 0.1,
+	    "dance_reduction": 0.99,
+	}
+	paras_prob_beesa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "recruited_bee_ratio": 0.1,
+	    "dance_radius": 0.1,
+	    "dance_reduction": 0.99,
+	}
+	paras_bes = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "a_factor": 10,
+	    "R_factor": 1.5,
+	    "alpha": 2.0,
+	    "c1": 2.0,
+	    "c2": 2.0,
+	}
+	paras_bfo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "Ci": 0.01,
+	    "Ped": 0.25,
+	    "Nc": 5,
+	    "Ns": 4,
+	    "d_attract": 0.1,
+	    "w_attract": 0.2,
+	    "h_repels": 0.1,
+	    "w_repels": 10,
+	}
+	paras_abfo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "C_s": 0.1,
+	    "C_e": 0.001,
+	    "Ped": 0.01,
+	    "Ns": 4,
+	    "N_adapt": 4,
+	    "N_split": 40,
+	}
+	paras_bsa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "ff": 10,
+	    "pff": 0.8,
+	    "c1": 1.5,
+	    "c2": 1.5,
+	    "a1": 1.0,
+	    "a2": 1.0,
+	    "fl": 0.5,
+	}
+	paras_coa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "n_coyotes": 5,
+	}
+	paras_csa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "p_a": 0.3,
+	}
+	paras_cso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "mixture_ratio": 0.15,
+	    "smp": 5,
+	    "spc": False,
+	    "cdc": 0.8,
+	    "srd": 0.15,
+	    "c1": 0.4,
+	    "w_min": 0.4,
+	    "w_max": 0.9,
+	    "selected_strategy": 1,
+	}
+	paras_do = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_eho = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "alpha": 0.5,
+	    "beta": 0.5,
+	    "n_clans": 5,
+	}
+	paras_fa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "max_sparks": 20,
+	    "p_a": 0.04,
+	    "p_b": 0.8,
+	    "max_ea": 40,
+	    "m_sparks": 5,
+	}
+	paras_ffa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "gamma": 0.001,
+	    "beta_base": 2,
+	    "alpha": 0.2,
+	    "alpha_damp": 0.99,
+	    "delta": 0.05,
+	    "exponent": 2,
+	}
+	paras_foa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_goa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "c_min": 0.00004,
+	    "c_max": 1.0,
+	}
+	paras_gwo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_hgs = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "PUP": 0.08,
+	    "LH": 10000,
+	}
+	paras_hho = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_ja = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_mfo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_mrfo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "somersault_range": 2.0,
+	}
+	paras_msa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "n_best": 5,
+	    "partition": 0.5,
+	    "max_step_size": 1.0,
+	}
+	paras_nmra = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pb": 0.75,
+	}
+	paras_improved_nmra = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pb": 0.75,
+	    "pm": 0.01,
+	}
+	paras_pfa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_pso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "c1": 2.05,
+	    "c2": 2.05,
+	    "w_min": 0.4,
+	    "w_max": 0.9,
+	}
+	paras_ppso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_hpso_tvac = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "ci": 0.5,
+	    "cf": 0.0,
+	}
+	paras_cpso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "c1": 2.05,
+	    "c2": 2.05,
+	    "w_min": 0.4,
+	    "w_max": 0.9,
+	}
+	paras_clpso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "c_local": 1.2,
+	    "w_min": 0.4,
+	    "w_max": 0.9,
+	    "max_flag": 7,
+	}
+	paras_sfo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pp": 0.1,
+	    "AP": 4.0,
+	    "epsilon": 0.0001,
+	}
+	paras_improved_sfo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "pp": 0.1,
+	}
+	paras_sho = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "h_factor": 5.0,
+	    "N_tried": 10,
+	}
+	paras_slo = paras_modified_slo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_improved_slo = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "c1": 1.2,
+	    "c2": 1.2
+	}
+	paras_srsr = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_ssa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "ST": 0.8,
+	    "PD": 0.2,
+	    "SD": 0.1,
+	}
+	paras_sso = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_sspidera = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "r_a": 1.0,
+	    "p_c": 0.7,
+	    "p_m": 0.1
+	}
+	paras_sspidero = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "fp_min": 0.65,
+	    "fp_max": 0.9
+	}
+	paras_woa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	}
+	paras_hi_woa = {
+	    "epoch": 20,
+	    "pop_size": 50,
+	    "feedback_max": 10
+	}
+
+	if __name__ == "__main__":
+		model = BBO.DevBBO(**paras_bbo)
+		model = BBO.OriginalBBO(**paras_bbo)
+		model = EOA.OriginalEOA(**paras_eoa)
+		model = IWO.OriginalIWO(**paras_eoa)
+		model = SBO.DevSBO(**paras_sbo)
+		model = SBO.OriginalSBO(**paras_sbo)
+		model = SMA.DevSMA(**paras_sma)
+		model = SMA.OriginalSMA(**paras_sma)
+		model = VCS.DevVCS(**paras_vcs)
+		model = VCS.OriginalVCS(**paras_vcs)
+		model = WHO.OriginalWHO(**paras_vcs)
+
+		model = CRO.OriginalCRO(**paras_cro)
+		model = CRO.OCRO(**paras_ocro)
+		# model = DE.BaseDE(**paras_de)
+		model = DE.JADE(**paras_jade)
+		model = DE.SADE(**paras_sade)
+		model = SHADE.OriginalSHADE(**paras_shade)
+		model = SHADE.L_SHADE(**paras_lshade)
+		model = DE.SAP_DE(**paras_sap_de)
+		model = EP.OriginalEP(**paras_ep)
+		model = EP.LevyEP(**paras_levy_ep)
+		model = ES.OriginalES(**paras_ep)
+		model = ES.LevyES(**paras_levy_ep)
+		model = FPA.OriginalFPA(**paras_fpa)
+		model = GA.BaseGA(**paras_ga)
+		model = GA.SingleGA(**paras_single_ga)
+		model = GA.MultiGA(**paras_multi_ga)
+		model = MA.OriginalMA(**paras_ma)
+
+		model = BRO.DevBRO(**paras_bro)
+		model = BRO.OriginalBRO(**paras_bro)
+		model = BSO.OriginalBSO(**paras_bso)
+		model = BSO.ImprovedBSO(**paras_improved_bso)
+		model = CA.OriginalCA(**paras_ca)
+		model = CHIO.DevCHIO(**paras_chio)
+		model = CHIO.OriginalCHIO(**paras_chio)
+		model = FBIO.DevFBIO(**paras_fbio)
+		model = FBIO.OriginalFBIO(**paras_fbio)
+		model = GSKA.DevGSKA(**paras_base_gska)
+		model = GSKA.OriginalGSKA(**paras_gska)
+		model = ICA.OriginalICA(**paras_ica)
+		model = LCO.DevLCO(**paras_lco)
+		model = LCO.OriginalLCO(**paras_lco)
+		model = LCO.ImprovedLCO(**paras_improved_lco)
+		model = QSA.DevQSA(**paras_qsa)
+		model = QSA.OriginalQSA(**paras_qsa)
+		model = QSA.OppoQSA(**paras_qsa)
+		model = QSA.LevyQSA(**paras_qsa)
+		model = QSA.ImprovedQSA(**paras_qsa)
+		model = SARO.DevSARO(**paras_saro)
+		model = SARO.OriginalSARO(**paras_saro)
+		model = SSDO.OriginalSSDO(**paras_ssdo)
+		model = TLO.DevTLO(**paras_tlo)
+		model = TLO.OriginalTLO(**paras_tlo)
+		model = TLO.ImprovedTLO(**paras_improved_tlo)
+
+		model = AOA.OriginalAOA(**paras_aoa)
+		model = CEM.OriginalCEM(**paras_cem)
+		model = CGO.OriginalCGO(**paras_cgo)
+		model = GBO.OriginalGBO(**paras_gbo)
+		model = HC.OriginalHC(**paras_hc)
+		model = HC.SwarmHC(**paras_swarm_hc)
+		model = PSS.OriginalPSS(**paras_pss)
+		model = SCA.OriginalSCA(**paras_sca)
+		model = SCA.DevSCA(**paras_sca)
+
+		model = HS.DevHS(**paras_hs)
+		model = HS.OriginalHS(**paras_hs)
+
+		model = AEO.OriginalAEO(**paras_aeo)
+		model = AEO.EnhancedAEO(**paras_aeo)
+		model = AEO.ModifiedAEO(**paras_aeo)
+		model = AEO.ImprovedAEO(**paras_aeo)
+		model = AEO.AugmentedAEO(**paras_aeo)
+		model = GCO.DevGCO(**paras_aeo)
+		model = GCO.OriginalGCO(**paras_aeo)
+		model = WCA.OriginalWCA(**paras_wca)
+
+		model = ArchOA.OriginalArchOA(**paras_archoa)
+		model = ASO.OriginalASO(**paras_aso)
+		model = EFO.OriginalEFO(**paras_efo)
+		model = EFO.DevEFO(**paras_efo)
+		model = EO.OriginalEO(**paras_eo)
+		model = EO.AdaptiveEO(**paras_eo)
+		model = EO.ModifiedEO(**paras_eo)
+		model = HGSO.OriginalHGSO(**paras_hgso)
+		model = MVO.OriginalMVO(**paras_mvo)
+		model = NRO.OriginalNRO(**paras_nro)
+		model = SA.OriginalSA(**paras_sa)
+		model = SA.SwarmSA(**paras_sa)
+		model = SA.GaussianSA(**paras_sa)
+		model = TWO.OriginalTWO(**paras_two)
+		model = TWO.OppoTWO(**paras_two)
+		model = TWO.LevyTWO(**paras_two)
+		model = TWO.EnhancedTWO(**paras_two)
+		model = WDO.OriginalWDO(**paras_wdo)
+
+		model = ABC.OriginalABC(**paras_abc)
+		model = ACOR.OriginalACOR(**paras_acor)
+		model = ALO.OriginalALO(**paras_alo)
+		model = AO.OriginalAO(**paras_ao)
+		model = ALO.DevALO(**paras_alo)
+		model = BA.OriginalBA(**paras_ba)
+		model = BA.AdaptiveBA(**paras_adaptive_ba)
+		model = BA.DevBA(**paras_dev_ba)
+		model = BeesA.OriginalBeesA(**paras_beesa)
+		model = BeesA.ProbBeesA(**paras_prob_beesa)
+		model = BES.OriginalBES(**paras_bes)
+		model = BFO.OriginalBFO(**paras_bfo)
+		model = BFO.ABFO(**paras_abfo)
+		model = BSA.OriginalBSA(**paras_bsa)
+		model = COA.OriginalCOA(**paras_coa)
+		model = CSA.OriginalCSA(**paras_csa)
+		model = CSO.OriginalCSO(**paras_cso)
+		model = DO.OriginalDO(**paras_do)
+		model = EHO.OriginalEHO(**paras_eho)
+		model = FA.OriginalFA(**paras_fa)
+		model = FFA.OriginalFFA(**paras_ffa)
+		model = FOA.OriginalFOA(**paras_foa)
+		model = FOA.DevFOA(**paras_foa)
+		model = FOA.WhaleFOA(**paras_foa)
+		model = GOA.OriginalGOA(**paras_goa)
+		model = GWO.OriginalGWO(**paras_gwo)
+		model = GWO.RW_GWO(**paras_gwo)
+		model = HGS.OriginalHGS(**paras_hgs)
+		model = HHO.OriginalHHO(**paras_hho)
+		model = JA.OriginalJA(**paras_ja)
+		model = JA.DevJA(**paras_ja)
+		model = JA.LevyJA(**paras_ja)
+		model = MFO.OriginalMFO(**paras_mfo)
+		# model = MFO.BaseMFO(**paras_mfo)
+		model = MRFO.OriginalMRFO(**paras_mrfo)
+		model = MSA.OriginalMSA(**paras_msa)
+		model = NMRA.ImprovedNMRA(**paras_improved_nmra)
+		model = NMRA.OriginalNMRA(**paras_nmra)
+		model = PFA.OriginalPFA(**paras_pfa)
+		model = PSO.OriginalPSO(**paras_pso)
+		model = PSO.P_PSO(**paras_ppso)
+		model = PSO.HPSO_TVAC(**paras_hpso_tvac)
+		model = PSO.C_PSO(**paras_cpso)
+		model = PSO.CL_PSO(**paras_clpso)
+		model = SFO.OriginalSFO(**paras_sfo)
+		model = SFO.ImprovedSFO(**paras_improved_sfo)
+		model = SHO.OriginalSHO(**paras_sho)
+		model = SLO.OriginalSLO(**paras_slo)
+		model = SLO.ModifiedSLO(**paras_modified_slo)
+		model = SLO.ImprovedSLO(**paras_improved_slo)
+		model = SRSR.OriginalSRSR(**paras_srsr)
+		model = SSA.OriginalSSA(**paras_ssa)
+		model = SSA.DevSSA(**paras_ssa)
+		model = SSO.OriginalSSO(**paras_sso)
+		model = SSpiderA.OriginalSSpiderA(**paras_sspidera)
+		model = SSpiderO.OriginalSSpiderO(**paras_sspidero)
+		model = WOA.OriginalWOA(**paras_woa)
+		model = WOA.HI_WOA(**paras_hi_woa)
+
+		g_best = model.solve(problem)
+		print(model.get_parameters())
+		print(model.get_name())
+		print(model.problem.get_name())
+		print(model.get_attributes()["g_best"])
 
 
 .. toctree::