Allow for prioritsation of items (cannot be in last/partial press)

data/glulam.csv

@@ -1,85 +1,85 @@
-order,quantity,depth,height,width,layers
-SP703563,5,115,315,4770,7
-SP703563,5,90,270,4935,6
-SP703563,10,160,315,5850,7
-SP703563,5,160,315,6600,7
-SP703563,5,160,315,6691,7
-SP703563,5,90,135,2463,3
-SP703563,5,115,315,9017,7
-SP703563,14,140,270,4820,6
-SP703563,5,185,360,5857,8
-SP703563,5,185,360,6693,8
-SP703563,5,185,360,5857,8
-SP703563,5,185,360,6693,8
-SP703563,5,115,225,2508,5
-SP703563,5,90,180,2508,4
-SP703563,8,140,270,948,6
-SP706182,17,140,315,4460,7
-SP706182,6,185,540,9200,12
-SP706182,10,140,315,4560,7
-SP706182,9,140,315,4460,7
-SP707443,6,185,225,3617,5
-SP707443,4,90,225,2100,5
-SP707443,7,185,225,3519,5
-SP707443,7,90,135,500,3
-SP707443,1,185,225,3617,5
-SP707443,2,185,225,3519,5
-SP707443,6,185,225,3939,5
-SP707443,2,185,180,3991,4
-SP707443,10,185,180,3963,4
-SP707443,2,185,180,3974,4
-SP707443,1,115,315,17689,7
-SP707443,1,115,315,11400,7
-SP707443,1,115,315,11041,7
-SP707443,1,115,315,7430,7
-SP707443,1,115,315,10793,7
-SP707443,1,140,270,3736,6
-SP707443,1,115,270,4178,6
-SP707443,2,90,180,3730,4
-SP707443,1,90,225,4204,5
-SP707443,5,90,225,3315,5
-SP707443,5,90,225,4000,5
-SP707443,5,90,225,3421,5
-SP707443,5,90,225,3440,5
-SP707443,4,90,225,3440,5
-SP707443,4,90,225,3358,5
-SP707443,8,90,180,3440,4
-SP708587,144,90,225,5013,5
-SP708587,24,140,225,4993,5
-SP708587,24,91,720,10215,16
-SP708587,24,91,1215,9981,27
-SP708587,36,115,135,5013,3
-SP708587,6,185,225,2357,5
-SP708587,8,90,180,2258,4
-SP708587,8,90,225,2144,5
-SP708587,4,140,225,2528,5
-SP708587,28,90,180,2548,4
-SP708587,8,90,180,2431,4
-SP708587,8,90,225,2339,5
-SP708587,28,90,225,5513,5
-SP708587,4,90,225,5495,5
-SP708587,5,140,225,5495,5
-SP708587,3,140,270,5331,6
-SP708587,24,140,180,4779,4
-SP708587,36,140,315,1048,7
-SP708587,36,90,225,1780,5
-SP708588,36,140,225,7586,5
-SP708588,16,90,225,4336,5
-SP708588,64,90,225,4363,5
-SP708588,4,140,225,4336,5
-SP708588,16,140,225,4363,5
-SP708588,4,115,315,4650,7
-SP708588,16,115,315,4600,7
-SP708588,20,140,225,3324,5
-SP708588,20,115,225,3324,5
-SP708588,20,115,180,3324,4
-SP708588,20,115,90,2500,2
-SP708588,20,115,90,1100,2
-SP708588,4,90,450,7677,10
-SP708588,4,90,450,3394,10
-SP708588,4,90,90,2881,2
-SP708588,4,140,90,2938,2
-SP708588,4,115,225,3618,5
-SP708588,4,115,225,3905,5
-SP708588,4,115,225,4190,5
-SP708588,4,115,225,4520,5
+order,quantity,depth,height,width,layers,priority
+SP703563,5,115,315,4770,7,FALSE
+SP703563,5,90,270,4935,6,FALSE
+SP703563,10,160,315,5850,7,FALSE
+SP703563,5,160,315,6600,7,FALSE
+SP703563,5,160,315,6691,7,FALSE
+SP703563,5,90,135,2463,3,FALSE
+SP703563,5,115,315,9017,7,FALSE
+SP703563,14,140,270,4820,6,FALSE
+SP703563,5,185,360,5857,8,FALSE
+SP703563,5,185,360,6693,8,FALSE
+SP703563,5,185,360,5857,8,FALSE
+SP703563,5,185,360,6693,8,FALSE
+SP703563,5,115,225,2508,5,FALSE
+SP703563,5,90,180,2508,4,FALSE
+SP703563,8,140,270,948,6,FALSE
+SP706182,17,140,315,4460,7,FALSE
+SP706182,6,185,540,9200,12,FALSE
+SP706182,10,140,315,4560,7,FALSE
+SP706182,9,140,315,4460,7,FALSE
+SP707443,6,185,225,3617,5,FALSE
+SP707443,4,90,225,2100,5,FALSE
+SP707443,7,185,225,3519,5,FALSE
+SP707443,7,90,135,500,3,FALSE
+SP707443,1,185,225,3617,5,FALSE
+SP707443,2,185,225,3519,5,FALSE
+SP707443,6,185,225,3939,5,FALSE
+SP707443,2,185,180,3991,4,FALSE
+SP707443,10,185,180,3963,4,FALSE
+SP707443,2,185,180,3974,4,FALSE
+SP707443,1,115,315,17689,7,FALSE
+SP707443,1,115,315,11400,7,FALSE
+SP707443,1,115,315,11041,7,FALSE
+SP707443,1,115,315,7430,7,FALSE
+SP707443,1,115,315,10793,7,FALSE
+SP707443,1,140,270,3736,6,FALSE
+SP707443,1,115,270,4178,6,FALSE
+SP707443,2,90,180,3730,4,FALSE
+SP707443,1,90,225,4204,5,FALSE
+SP707443,5,90,225,3315,5,FALSE
+SP707443,5,90,225,4000,5,FALSE
+SP707443,5,90,225,3421,5,FALSE
+SP707443,5,90,225,3440,5,FALSE
+SP707443,4,90,225,3440,5,FALSE
+SP707443,4,90,225,3358,5,FALSE
+SP707443,8,90,180,3440,4,FALSE
+SP708587,144,90,225,5013,5,FALSE
+SP708587,24,140,225,4993,5,FALSE
+SP708587,24,91,720,10215,16,FALSE
+SP708587,24,91,1215,9981,27,FALSE
+SP708587,36,115,135,5013,3,FALSE
+SP708587,6,185,225,2357,5,FALSE
+SP708587,8,90,180,2258,4,FALSE
+SP708587,8,90,225,2144,5,FALSE
+SP708587,4,140,225,2528,5,FALSE
+SP708587,28,90,180,2548,4,FALSE
+SP708587,8,90,180,2431,4,FALSE
+SP708587,8,90,225,2339,5,FALSE
+SP708587,28,90,225,5513,5,FALSE
+SP708587,4,90,225,5495,5,FALSE
+SP708587,5,140,225,5495,5,FALSE
+SP708587,3,140,270,5331,6,FALSE
+SP708587,24,140,180,4779,4,FALSE
+SP708587,36,140,315,1048,7,FALSE
+SP708587,36,90,225,1780,5,FALSE
+SP708588,36,140,225,7586,5,FALSE
+SP708588,16,90,225,4336,5,FALSE
+SP708588,64,90,225,4363,5,FALSE
+SP708588,4,140,225,4336,5,FALSE
+SP708588,16,140,225,4363,5,FALSE
+SP708588,4,115,315,4650,7,FALSE
+SP708588,16,115,315,4600,7,FALSE
+SP708588,20,140,225,3324,5,FALSE
+SP708588,20,115,225,3324,5,FALSE
+SP708588,20,115,180,3324,4,FALSE
+SP708588,20,115,90,2500,2,FALSE
+SP708588,20,115,90,1100,2,FALSE
+SP708588,4,90,450,7677,10,FALSE
+SP708588,4,90,450,3394,10,FALSE
+SP708588,4,90,90,2881,2,FALSE
+SP708588,4,140,90,2938,2,FALSE
+SP708588,4,115,225,3618,5,FALSE
+SP708588,4,115,225,3905,5,FALSE
+SP708588,4,115,225,4190,5,FALSE
+SP708588,4,115,225,4520,5,FALSE

main.py

@@ -46,7 +46,6 @@ def main(file_path, depth, name, run, mode, overwrite):
         return
 
 
-
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Glulam Production Optimizer")
     parser.add_argument(

models/pack_n_press.py

@@ -26,11 +26,11 @@ def cb(model, where):
     """
     if where == gp.GRB.Callback.MIP:
         # Check if a feasible solution is found
-        if model.cbGet(gp.GRB.Callback.MIP_SOLCNT) > 0 and not hasattr(model, '_feasible_time'):
-            model._feasible_time = time.time()
+        if model.cbGet(gp.GRB.Callback.MIP_SOLCNT) > 0 and not hasattr(model, '_feasible'):
+            model._feasible = time.time()
             model._time = time.time()
             logger.info(
-                f"First feasible solution found after {(model._feasible_time - model._start_time) / 60:.2f} minutes.")
+                f"First feasible solution found after {(model._feasible - model._start_time) / 60:.2f} minutes.")
 
     if where == gp.GRB.Callback.MIPNODE:
         # Get model objective
@@ -43,14 +43,15 @@ def cb(model, where):
             model._time = time.time()
 
     # Terminate if a feasible solution has been found and no improvement for over a minute
-    if hasattr(model, '_feasible_time') and model._feasible_time:
+    if hasattr(model, '_feasible') and model._feasible:
         if time.time() - model._time > GlulamConfig.GUROBI_NO_IMPROVEMENT_TIME_LIMIT:
-            model._terminated_early = time.time()
             model.terminate()
-            logger.warning(f"Terminating optimization: no improvement for over "
-                           f"{GlulamConfig.GUROBI_NO_IMPROVEMENT_TIME_LIMIT / 60:.0f} minute. "
-                           f"Elapsed time since first feasible solution: "
-                           f"{(model._terminated_early - model._feasible_time) / 60:.2f} minutes.")
+            if not hasattr(model, '_terminated'):
+                model._terminated = time.time()
+                logger.warning(f"Terminating optimization: no improvement for over "
+                               f"{GlulamConfig.GUROBI_NO_IMPROVEMENT_TIME_LIMIT / 60:.0f} minute. "
+                               f"Elapsed time since first feasible solution: "
+                               f"{(model._terminated - model._feasible) / 60:.2f} minutes.")
 
 
 class GlulamPackagingProcessor:
@@ -137,6 +138,14 @@ def RW(self):
     def I(self):
         return self.patterns.I
 
+    @property
+    def I_priority(self):
+        """
+        The set of orders that are prioritized. I_priority ⫋ I.
+        They that cannot be in the last press (which can be a partial press).
+        """
+        return self.patterns.data.priority_items
+
     @property
     def J(self):
         return self.patterns.J
@@ -186,6 +195,7 @@ def pack_n_press(self, time_limit=GlulamConfig.GUROBI_TIME_LIMIT):
         self.x = None
         self.xn = None
         self.h = None
+        self.run_summary = None
 
         # parameters
         bigM = 1e8  # a big number
@@ -275,13 +285,19 @@ def pack_n_press(self, time_limit=GlulamConfig.GUROBI_TIME_LIMIT):
         # make sure that the length of the region is at least the length of the longest pattern in use
         pmodel.addConstrs(Lp[k, r] >= x1[j, k, r] * self.L[j] for j in self.J for r in self.R for k in self.K)
 
+        # Ensure priority items are not produced in the last press
+        for j in self.J:
+            if any(self.A[i, j] > 0 for i in self.I_priority):  # This pattern produces a priority item
+                pmodel.addConstrs(
+                    (x1[j, k, r] == 0 for k in self.K[:-1] for r in self.R), name="no_priority_in_last_press")
+
         # define the surplus of each pattern in each press and region as the difference between the length of the
         # pattern and the length of the region
         pmodel.addConstrs(
             ((Lp[k, r] - self.L[j]) * self.H[j] <= F[j, k, r] + (1 - x1[j, k, r]) * bigM
              for j in self.J for k in self.K for r in self.R), name="F_surplus_definition")
 
-        # now we add the objective function as the sum of waste for all presses and the difference between demand and supply
+        # the objective function as the sum of waste for all presses and the difference between demand and supply
         pmodel.setObjective(
             gp.quicksum(F[j, k, r] for j in self.J for k in self.K for r in self.R)
             , gp.GRB.MINIMIZE)
@@ -331,6 +347,23 @@ def pack_n_press(self, time_limit=GlulamConfig.GUROBI_TIME_LIMIT):
             axis=0)  # Waste in m^2
         logger.info(f'Total waste: {self.TotalWaste:.3f} m^2')
         logger.debug(f'Waste:\n{self.Waste}')
+
+        # Maintain a summary of the run
+        self.run_summary = {
+            'time': int(time.time() - pmodel._start_time),
+            'first_feasible': int(pmodel._feasible - pmodel._start_time) if hasattr(pmodel, '_feasible') else None,
+            'terminated_early': int(pmodel._terminated - pmodel._feasible) if hasattr(pmodel, '_terminated') else None,
+            'nconstrs': pmodel.NumConstrs,
+            'nvars': pmodel.NumVars,
+            'status': pmodel.status,
+            'npatterns': self.patterns.n,
+            'norders': self.patterns.m,
+            'npresses': self.number_of_presses,
+            'npresses_used': np.sum(self.presses_in_use),
+            'objective': self.ObjectiveValue,
+            'total_waste': self.TotalWaste,
+        }
+
         return True
 
     def print_results(self):

slurm.sh

@@ -1,8 +1,8 @@
 #!/bin/bash
 
 # Default values
-hours=5
-cpus=48
+hours=8
+cpus=12
 mem=3900
 partition=48cpu_192mem
 
@@ -31,12 +31,11 @@ cat > "$job_script" <<EOF
 #SBATCH --cpus-per-task=${cpus}
 #SBATCH --mem-per-cpu=${mem}
 #SBATCH --time=${hours}:00:00
-#SBATCH --output=data/slurm/%x_%j_%a.out
-#SBATCH --error=data/slurm/%x_%j_%a.err
+#SBATCH --output=data/slurm/%x_%a_%j.out
+#SBATCH --error=data/slurm/%x_%a_%j.err
 #SBATCH --array=1-${runs}%${max_sessions}
 
 # Run the command for this array job
-echo make data/$version/soln_ES_d${depth}_\${SLURM_ARRAY_TASK_ID}.json depth=${depth} run=\${SLURM_ARRAY_TASK_ID} VERSION=${version}
 make data/$version/soln_ES_d${depth}_\${SLURM_ARRAY_TASK_ID}.json depth=${depth} run=\${SLURM_ARRAY_TASK_ID} VERSION=${version}
 EOF
 

strategies/evolution_strategy.py

@@ -164,10 +164,11 @@ def Objective(self):
 
         return objective, press
 
-    def _add_stats(self, x, sigma, gen, current_obj):
+    def _add_stats(self, x, sigma, gen, press):
         if self.stats is None:
             self.stats = {'xstar': [], 'sstar': [], 'sucstar': [], 'waste': [], 'npresses': [], 'x': [], 'sigma': [],
-                          'gen': [], 'npatterns': [], 'objective': []}
+                          'gen': [], 'run_summary': []
+                          }
         self.stats['xstar'].append(self.xstar)
         self.stats['sstar'].append(self.sstar)
         self.stats['sucstar'].append(self.sucstar)
@@ -176,8 +177,7 @@ def _add_stats(self, x, sigma, gen, current_obj):
         self.stats['x'].append(x)
         self.stats['sigma'].append(sigma)
         self.stats['gen'].append(gen)
-        self.stats['npatterns'].append(self.merged.n)
-        self.stats['objective'].append(current_obj)
+        self.stats['run_summary'].append(press.run_summary)
         logger.info(
             f"Stats - Generation {gen} - waste = {self.waste}, npresses = {self.npresses}, "
             f"xstar = {self.xstar} (#{len(self.xstar)})")
@@ -197,7 +197,7 @@ def Search(self, filename, x=None):
         def save_results(filename):
             """ Save results to json. """
             results = {'roll_widths': self.xstar, 'presses': self.npresses, 'waste': self.waste, 'stats': self.stats,
-                       'depth': self.merged.data.depth, 'n': self.merged.n, 'm': self.merged.m}
+                       'depth': self.merged.data.depth }
             with open(filename, 'w') as f:
                 json.dump(convert_numpy_to_json(results), f, indent=4)
             logger.info(f"Saved the solution to {filename}")
@@ -231,7 +231,7 @@ def save_results(filename):
         self.Selection(x, sigma, success, press)
 
         # now lets start the search, for max max_generations
-        self._add_stats(x, sigma, 0, (self.waste, self.npresses))
+        self._add_stats(x, sigma, 0, press)
         for gen in range(1, self.max_generations):
             logger.info(f"Generation: {gen}/{self.max_generations}")
 
@@ -289,7 +289,7 @@ def save_results(filename):
                     logger.info(f"NEW BEST: the successes are {self.sucstar}")
                     logger.info(f"NEW BEST: the number of patterns is {self.merged.n}")
 
-            self._add_stats(x, sigma, gen, (waste_, npresses_))
+            self._add_stats(x, sigma, gen, press)
             save_results(filename + ".part")
 
         logger.info(f"Search - Finished the search after {self.max_generations} generations.")

utils/data_processor.py

@@ -28,6 +28,13 @@ def __init__(self, file_path, depth):
         # Reset index
         self._filtered_data.reset_index(drop=True, inplace=True)
 
+        # Priority items are those defined in the file, but if they are all the same order, then there is no priority
+        # it is the index for the items with column 'priority' set to True (but only if there are some items with False)
+        self._priority_items = []
+        priority_items = self._filtered_data['priority']
+        if priority_items.any() and not priority_items.all():
+            self._priority_items = np.where(priority_items)[0]
+
     @property
     def area(self):
         """ Compute the minimum area needed to fit all orders in square meters. """
@@ -68,6 +75,11 @@ def orders(self):
         """ Set of orders. """
         return sorted(list(set(self.order.tolist())))
 
+    @property
+    def priority_items(self):
+        """ Set of priority items. """
+        return self._priority_items
+
 
 def convert_numpy_to_json(items):
     """ Convert numpy types to json compatible types. """
@@ -81,4 +93,3 @@ def convert_numpy_to_json(items):
         return {k: convert_numpy_to_json(v) for k, v in items.items()}
     if isinstance(items, int) or isinstance(items, float) or isinstance(items, str):
         return items
-