This repository is a collection of mathematical optimization algorithms and solutions for a variety of optimization problems. It provides a toolkit of algorithms and techniques for tackling optimization challenges in different domains.
- Gradient-Descent: Implementation of the gradient descent algorithm for optimization. 📈
- Simplex-Method-With-Artificial-Variables: Implementation of the simplex method with artificial variables for linear programming. 📊
- Golden-Section-Search: Implementation of the golden section search algorithm for one-dimensional optimization. 🌟
- Transportation-Problem: Implementation of algorithms for solving transportation problems. 🚚
- Linear-Regression: Implementation of linear regression algorithms with support for optimization methods. 📈
- Distribution-Of-Investments: Implementation of algorithms for optimizing the distribution of investments. 💰
Feel free to explore each directory to find the specific algorithms and implementations. Each directory contains detailed explanations and code examples for solving optimization problems using various algorithms.
To use any of the algorithms or solutions in this repository, navigate to the respective directory and find the corresponding Python file(s). Each file includes a clear explanation and usage instructions. Make sure you have Python installed on your system to run the code.
Contributions to this repository are welcome! If you have any improvements, bug fixes, or new algorithms to contribute, please feel free to submit a pull request.
Let's optimize the world together! 🌍💪