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by Dorit S. Hochbaum (Editor)
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Reviews Book Description With chapters contributed by leading researchers in the field, this book provides computer scientists and operations researchers with an effective framework for analyzing approximation algorithms and applying them to the solution of very large, complex problems. Each chapter examines a specific application area--including scheduling, network design, connectivity problems, low-degree structures, Euclidian problems, on-line problems, covering and packing problems, counting problems, multicommodity problems, and bin packing problems--and explores unifying problem-solving techniques. These techniques, whose applicability to such a wide range of fields has emerged only recently, include linear programming, primal-dual techniques in worst-case analysis, semidefinite programming, computational geometry techniques, randomized algorithms, average-case analysis, probabilistically checkable proofs and inapproximability, and the Markov Chain Monte Carlo method.
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Copyright (c) by Eugene Kisly and Victor Kisly , 1999-2000
