Dantzig’s simplex algorithm, duality, sensitivity analysis, integer optimization models, and network models are introduced. The first covers the theory of linear and integer optimization, including both basic and advanced topics. c o m Sierksma and Zwols “.very recommendable as a textbook and to anybody wishing to learn the topic.” -Optimization (1997) LINEAR AND INTEGER OPTIMIZATION Presenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. Praise for the first edition: “.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) K25031 w w w. 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. All chapters contain extensive examples and exercises. This new edition also contains appendices covering mathematical proofs, linear algebra, graph theory, convexity, and nonlinear optimization. The models and corresponding data files are available for download and can be readily solved using the provided online solver. The book now includes computer code in the form of models in the GNU Mathematical Programming Language (GMPL). Besides the fresh new layout and completely redesigned figures, this new edition incorporates modern examples and applications of linear optimization. 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. The second part applies theory through real-world case studies.

More advanced topics also are presented including interior point algorithms, the branchand-bound algorithm, cutting planes, complexity, standard combinatorial optimization models, the assignment problem, minimum cost flow, and the maximum flow/minimum cut theorem.

Table of contents : 1 Basic concepts of linear optimization.1 Linear optimization theory basic techniques.49 Linear optimization practice advanced techniques.411 Appendices.561 Citation preview

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