By Yamal 
Linear programming is a powerful mathematical technique used for optimization, especially when faced with resource allocation issues. If you’re looking to dive deeper into this field, here are some of the best books to help you learn linear programming:
- “Introduction to Operations Research” by Frederick S. Hillier and Gerald J. Lieberman
This comprehensive textbook covers various topics in operations research, including linear programming. It offers a solid theoretical foundation along with practical applications.
- “Linear Programming: Foundations and Extensions” by Robert J. Vanderbei
This book provides a thorough introduction to linear programming and its advanced topics. It’s suitable for both beginners and those with some background knowledge.
- “Operations Research: An Introduction” by Hamdy A. Taha
Taha’s book is an excellent resource that introduces linear programming within the context of operations research. The explanations are clear and come with a variety of real-world examples.
- “Linear Programming” by George B. Dantzig and Mukund N. Thapa
Written by the pioneer of linear programming himself, this book offers insight into the methodology and applications of the subject, making it a classic choice for learners.
- “Convex Optimization” by Stephen Boyd and Lieven Vandenberghe
While broader than just linear programming, this book offers a modern take on optimization techniques, including a deep dive into convex sets and functions, which are crucial for understanding linear programming.
- “Applied Linear Programming” by Michael E. Atlas
This practical guide emphasizes the application of linear programming to real-world scenarios, making it particularly useful for those looking to apply their knowledge immediately.
These books collectively cater to various learning styles, whether you prefer theoretical insights or practical applications. Select one or several of them based on your current understanding and goals in mastering linear programming. Happy reading!