Optimization is a powerful technique that is used to solve systems of linear/non-linear equations and inequalities while maximizing or minimizing some functions. It is used in a wide array of data science problems from inventory optimization to dynamic pricing. In python, there are several tools available for solving these problems which can be a bit overwhelming for a new learner as each has its own limitations along with code implementation.

To address this issue, I have created a GitHub repository with solutions for various optimization techniques such as Linear and Non-Linear programming, Constraint programming, Second Order Cone Programming and Genetic algorithm. I have created the solutions primarily using Pyomo and ORTools. I have also included a few case studies which I solved using traditional and non-traditional approaches. For example, route optimization is an extremely popular problem which is typically solved with ORTools from Google. Apart from solving it using ORTools, I have also created solutions using Constraint programming.

Link for the Github repository: https://lnkd.in/gn6svjeS

I hope this will help new learners in better understanding the intuition behind problems and formulating the algorithms.

Please feel free to navigate the repository and comment for any improvement or suggestions.

#datascience #python #optimization #linearprogramming