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Linear and Integer Optimization: Theory and Practice, Third Edition: Advances in Applied Mathematics

Autor Gerard Sierksma, Yori Zwols
en Limba Engleză Hardback – mai 2015
Presenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig’s simplex algorithm, duality, sensitivity analysis, integer optimization models, and network models are introduced.
More advanced topics also are presented including interior point algorithms, the branch-and-bound algorithm, cutting planes, complexity, standard combinatorial optimization models, the assignment problem, minimum cost flow, and the maximum flow/minimum cut theorem.
The second part applies theory through real-world case studies. The authors discuss advanced techniques such as column generation, multiobjective optimization, dynamic optimization, machine learning (support vector machines), combinatorial optimization, approximation algorithms, and game theory.
Besides the fresh new layout and completely redesigned figures, this new edition incorporates modern examples and applications of linear optimization. The book now includes computer code in the form of models in the GNU Mathematical Programming Language (GMPL). The models and corresponding data files are available for download and can be readily solved using the provided online solver.
This new edition also contains appendices covering mathematical proofs, linear algebra, graph theory, convexity, and nonlinear optimization. All chapters contain extensive examples and exercises. This textbook is ideal for courses for advanced undergraduate and graduate students in various fields including mathematics, computer science, industrial engineering, operations research, and management science.
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Specificații

ISBN-13: 9781498710169
ISBN-10: 1498710166
Pagini: 686
Ilustrații: 175 black & white illustrations, 60 black & white tables
Dimensiuni: 178 x 254 x 38 mm
Greutate: 1.59 kg
Ediția:Revised
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Advances in Applied Mathematics

Locul publicării:Boca Raton, United States

Cuprins

Basic Concepts of Linear Optimization. LINEAR OPTIMIZATION THEORY: BASIC TECHNIQUES. Geometry and Algebra of Feasible Regions. Dantzig’s Simplex Algorithm. Duality, Feasibility, and Optimality. Sensitivity Analysis. Large-Scale Linear Optimization. Integer Linear Optimization. Linear Network Models. Computational Complexity. LINEAR OPTIMIZATION PRACTICE: ADVANCED TECHNIQUES. Designing a Reservoir for Irrigation. Classifying Documents by Language. Production Planning; A Single Product Case. Production of Coffee Machines. Conflicting Objectives: Producing Versus Importing. Coalition Formation and Profit Distribution. Minimizing Trimloss When Cutting Cardboard. Off-Shore Helicopter Routing. The Catering Service Problem. Appendix A Mathematical Proofs. Appendix B Linear Algebra. Appendix C Graph Theory. Appendix D Convexity. Appendix E Nonlinear Optimization. Appendix F Writing LO-Models in GNU MathProg (GMPL). List of Symbols. Bibliography.

Notă biografică

Gerard Sierksma, PhD, University of Groningen, The Netherlands
Yori Zwols, PhD, Google UK, London

Recenzii

Praise for the first edition:

"...very recommendable as a textbook and to anybody wishing to learn the topic."
Optimization (1997)

"...the book is a nice balance between theory and applications...and gives a sound background for the techniques used and for investigating real problems."
Zentralblatt für Mathematik (1998)


Descriere

This textbook presents a strong and clear relationship between theory and practice. It covers basic topics such as Dantzig’s simplex algorithm, duality, sensitivity analysis, integer optimization models, and network models as well as more advanced topics including interior point algorithms, the branch-and-bound algorithm, cutting planes, and complexity. Along with case studies, it also discusses more advanced techniques such as column generation, multiobjective optimization, and game theory. It also includes computer code in the form of models in GMPL. The book contains appendices covering mathematical proofs, linear algebra, graph theory, convexity, and a background in nonlinear optimization. All chapters contain extensive examples and exercises.
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