Synopsis
This book treats the fundamental issues and algorithmic strategies emerging as the core of the discipline of discrete optimization in a comprehensive and rigorous fashion. Following an introductory chapter on computational complexity, the basic algorithmic results for the two major models of polynomial algorithms are introduced--models using matroids and linear programming. Further chapters treat the major non-polynomial algorithms: branch-and-bound and cutting planes. The text concludes with a chapter on heuristic algorithms.Several appendixes are included which review the fundamental ideas of linear programming, graph theory, and combinatorics--prerequisites for readers of the text. Numerous exercises are included at the end of each chapter.
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Review
Accessible to students, researchers, and instructors, this work would be valuable both for a university course in discrete optimization and as a reference book. The references are good and up to date.--COMPUTING REVIEWSThe book is cleary and beautifully written. It is a very useful reference on the subject and can be used as an advanced graduate text for courses in combinatorial or discrete optimization.--MATHEMATICAL REVIEWS
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Discrete Optimization (Computer Science and Scientific Computing)
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