Models and Methods in Linear Optimization David J. Rader Jr. is a study book focused on operations research and algorithm design for linear optimization. It addresses the modeling and solving of linear optimization problems with a combination of mathematical theory and practical algorithmics.
The book offers a clear introduction to deterministic operations research, with an emphasis on the development of algorithms for continuous and discrete linear problems. Three pillars are central: modeling real-world situations as linear optimization problems, designing the corresponding algorithms, and using mathematical theory to underpin them.
Contents
The text covers examples from various sectors, including sports scheduling and aviation, and addresses essential concepts such as convexity, Farkas' Lemma, polyhedral theory, the Simplex method, and duality theory. In addition, advanced methods such as the Dual Simplex, Dantzig-Wolfe decomposition, and primal-dual interior point algorithms are discussed. It concludes with network optimization and integer programming, including techniques such as label-correcting algorithms and branch-and-cut methods.
Concepts are introduced through examples, making the theory accessible and contributing to a better understanding of algorithm design for linear optimization. The book also includes relevant historical overviews and practical models, supported by digital computation examples in Maple and MATLAB.
Product specifications
- Author: David J. Rader (Rose-Hulman Institute of Technology)
- Publisher: John Wiley & Sons Inc
- Publication date: 2010-08-06
- Number of pages: 632
- ISBN: 9780470484517
- Topic: Linear programming
- BISAC: MATHEMATICS / Linear & Nonlinear Programming