Iterative Methods in Combinatorial Optimization

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Format: Paperback
Pub. Date: 2011-04-18
Publisher(s): Cambridge University Press
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Summary

With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence, and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids, and flows. The presentation style is elementary enough to be accessible to anyone with exposure to basic linear algebra and graph theory, making the book suitable for introductory courses in combinatorial optimization at the upper undergraduate and beginning graduate levels. Discussions of advanced applications illustrate their potential for future application in research in approximation algorithms.

Table of Contents

Prefacep. ix
Introductionp. 1
The assignment problemp. 1
Iterative algorithmp. 3
Approach outlinep. 5
Context and applications of iterative roundingp. 8
Book chapters overviewp. 8
Notesp. 10
Preliminariesp. 12
Linear programmingp. 12
Graphs and digraphsp. 19
Submodular and supermodular functionsp. 21
Matching and vertex cover in bipartite graphsp. 28
Matchings in bipartite graphsp. 28
Generalized assignment problemp. 32
Maximum budgeted allocationp. 35
Vertex cover in bipartite graphsp. 40
Vertex cover and matching: dualityp. 43
Notesp. 44
Spanning treesp. 46
Minimum spanning treesp. 46
Iterative 1-edge-finding algorithmp. 54
Minimum bounded-degree spanning treesp. 57
An additive one approximation algorithmp. 60
Notesp. 62
Matroidsp. 65
Preliminariesp. 65
Maximum weight basisp. 67
Matroid intersectionp. 71
Duality and min-max theoremp. 74
Minimum bounded degree matroid basisp. 77
k matroid intersectionp. 82
Notesp. 85
Arborescence and rooted connectivityp. 88
Minimum cost arborescencep. 89
Minimum cost rooted k-connected subgraphsp. 95
Minimum bounded degree arborescencep. 101
Additive performance guaranteep. 106
Notesp. 108
Submodular flows and applicationsp. 110
The model and the main resultp. 110
Primal integralityp. 112
Dual integralityp. 116
Applications of submodular flowsp. 117
Minimum bounded degree submodular flowsp. 124
Notesp. 128
Network matricesp. 131
The model and main resultsp. 131
Primal integralityp. 133
Dual integralityp. 136
Applicationsp. 139
Notesp. 143
Matchingsp. 145
Graph matchingp. 145
Hypergraph matchingp. 155
Notesp. 160
Network designp. 164
Survivable network design problemp. 164
Connection to the traveling salesman problemp. 168
Minimum bounded degree Steiner networksp. 172
An additive approximation algorithmp. 175
Notesp. 179
Constrained optimization problemsp. 182
Vertex coverp. 182
Partial vertex coverp. 184
Multicriteria spanning treesp. 187
Notesp. 189
Cut problemsp. 191
Triangle coverp. 191
Feedback vertex set on bipartite tournamentsp. 194
Node multiway cutp. 197
Notesp. 200
Iterative relaxation: Early and recent examplesp. 203
A discrepancy theoremp. 203
Rearrangments of sumsp. 206
Minimum cost circulationp. 208
Minimum cost unsplittable flowp. 210
Bin packingp. 212
Iterative randomized rounding: Steiner treesp. 220
Notesp. 228
Summaryp. 231
Bibliographyp. 233
Indexp. 241
Table of Contents provided by Ingram. All Rights Reserved.

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