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General optimization (LP, MIP, QP, continuous and discrete optimization etc.) using Python

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Name		Name	Last commit message	Last commit date
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images		images
.gitignore		.gitignore
Balanced_Diet_Problem_Complex.ipynb		Balanced_Diet_Problem_Complex.ipynb
Balanced_Diet_Problem_Medium.ipynb		Balanced_Diet_Problem_Medium.ipynb
Balanced_Diet_Problem_Simple.ipynb		Balanced_Diet_Problem_Simple.ipynb
LICENSE		LICENSE
Portfolio_optimization.ipynb		Portfolio_optimization.ipynb
PuLP_practice.ipynb		PuLP_practice.ipynb
README.md		README.md
SciPy_optimization.ipynb		SciPy_optimization.ipynb
Scipy-Linear-Programming.ipynb		Scipy-Linear-Programming.ipynb
Simulation-interpolation.ipynb		Simulation-interpolation.ipynb

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Optimization-Python

General optimization (LP, MIP, QP etc.) examples using Python.

Fast optimization for complex simulations using Scipy interpolate

Please feel free to connect with me here on LinkedIn if you are interested in data science, machine learning.

Requirements

Python 3+
scipy (pip install scipy)
numpy (pip install numpy)
PuLP (pip install pulp)
CVXPY (pip install cvxpy)

My Medium articles on optimization

Read my article on Medium about optimization in machine learning algorithms

Read my article on Medium about optimization with SciPy

Read my article on Medium about stock market portfolio optimization with CVXPY

Read my article on Medium about linear programming with PuLP

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General optimization (LP, MIP, QP, continuous and discrete optimization etc.) using Python

optimization linear-programming scipy quadratic-programming convex-optimization integer-programming mixed-integer-programming

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