A Guide to Learning Linear Programming

This book was written as an informal tutorial to learning linear programming and consists of easy-to-read chapters that prepare readers' mindsets for how they should think about optimization problems and what questions they should be asking. As an example, far too much emphasis is put on finding an optimal solution and not enough emphasis is put on reduced costs and shadow prices. If readers see these three items as equally important components, they tend to learn the material much more naturally. This book also anticipates where readers typically become confused or lost and explores several examples (with step-by-step analysis) that guide them back in the right direction. This approach comes from the author's years of teaching experience where he observed the learning patterns of his students. For example, he learned both where students become confused on new concepts and when students tend to forget related material that was learned before. The format of each chapter is consistent throughout to aid in reader comprehension and includes: an overview section that reviews what the chapter will cover, what the reader should be expect, and the vital concepts that should be known prior to reading on. Example questions are provided at the end of each sub-section in addition to the three most important concepts that should have been learned from reading the section. In an effort to provide applicability to the discussed concepts, each chapter also provides real world situations. Topical coverage includes mathematical models; common mathematical modeling tricks; basics of liner programming; the simplex method; foundations and applications in duality; duality in network flows; and extensions and modern techniques.