Welcome to the Optimization repository! This is a collection of optimization codes, started with my desire as an educator to understand the behind-the-scenes of the most popular algorithms in Optimization and to provide resources to my students. I have provided real-world cases that readers and visitors can modify according to their specific needs although most of them revolving in the Finance industry.
Optimization is simply about finding the best course of action for a given problem.
The repository is structured into different sections, covering various facets of optimization:
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... and many more!
- Browse Through Folders: Each folder corresponds to a different optimization technique or topic. Start with the one you're most interested in.
- Run Code: Most of the codes are provided with sample data. You can run them to see how they perform and then modify or tweak as per your requirements.
- Read Comments: The codes come with comprehensive comments to help you understand each step of the optimization process.
- Contribute: Feel free to contribute by either improving existing codes, adding new ones, or even improving this documentation.
- Familiarity with programming, preferably in Python or MATLAB (as most codes are written in these languages).
- Basic understanding of mathematical optimization concepts.
The codes might require specific libraries or toolboxes depending on the programming language used. Please ensure you check the comments or the respective requirements.txt file (for Python codes) before running the programs.
Contributions are more than welcome! Here's how you can help:
- Fork the repository.
- Create a new branch.
- Add or modify codes.
- Create a pull request.
Before contributing, please ensure you have:
- Commented your code properly.
- Added a brief description of your contribution in the pull request.
For those new to optimization, here are some book recommendations:
- "Introduction to Operations Research" by Hillier and Lieberman.
- "Convex Optimization" by Stephen Boyd and Lieven Vandenberghe.
- "Nonlinear Programming: Theory and Algorithms" by Mokhtar S. Bazaraa, Hanif D. Sherali, and C. M. Shetty.
For queries, suggestions, or feedback, feel free to reach out at my personal email.
⭐ If you find this repository helpful, please consider giving it a star. Happy optimizing!