Network flow algorithms

Network flow algorithms

by Williamson, David P.

Type Book
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Network flow theory has been used across a number of disciplines, including theoretical computer science, operations research, and discrete math, to model not only problems in the transportation of goods and information, but also a wide range of applications from image segmentation problems in computer vision to deciding when a baseball team has been eliminated from contention. This graduate text and reference presents a succinct, unified view of a wide variety of efficient combinatorial algori…

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Title Statements

  • Full title :Network flow algorithms / David P. Williamson.

Summary

Network flow theory has been used across a number of disciplines, including theoretical computer science, operations research, and discrete math, to model not only problems in the transportation of goods and information, but also a wide range of applications from image segmentation problems in computer vision to deciding when a baseball team has been eliminated from contention. This graduate text and reference presents a succinct, unified view of a wide variety of efficient combinatorial algorithms for network flow problems, including many results not found in other books. It covers maximum flows, minimum-cost flows, generalized flows, multicommodity flows, and global minimum cuts and also presents recent work on computing electrical flows along with recent applications of these flows to classical problems in network flow theory.

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Edition Statements

  • Publication Date:2019.

Publication Statements

Notes

Title from publisher's bibliographic system (viewed on 26 Aug 2019).

The Physical Object

  • Description:1 online resource (xii, 314 pages) : : PDF file(s).

Edition Identifiers

  • ISBN:9781316888568, 1316888568
  • oclc:on1233263412
  • LC Classification:T57.85
  • Dewey Decimal:003

Table of Contents

Cover -- Half-title -- Frontispiece -- Title page -- Copyright information -- Contents -- Preface -- Acknowledgments -- 1 Preliminaries: Shortest Path Algorithms -- 1.1 Nonnegative Costs: Dijkstra's Algorithm -- 1.2 Negative Costs: The Bellman-Ford Algorithm -- 1.3 Negative-Cost Cycle Detection -- Exercises -- Chapter Notes -- 2 Maximum Flow Algorithms -- 2.1 Optimality Conditions -- 2.2 Application: Carpool Sharing -- 2.3 Application: The Baseball Elimination Problem -- 2.4 Application: Finding a Maximum Density Subgraph -- 2.5 Most Improving Augmenting Paths -- 2.6 A Capacity Scaling Algorithm -- 2.7 Shortest Augmenting Paths -- 2.8 The Push-Relabel Algorithm -- Exercises -- Chapter Notes -- 3 Global Minimum Cut Algorithms -- 3.1 The Hao-Orlin Algorithm -- 3.2 The MA Ordering Algorithm -- 3.3 The Random Contraction Algorithm -- 3.4 The Gomory-Hu Tree -- Exercises -- Chapter Notes -- 4 More Maximum Flow Algorithms -- 4.1 Blocking Flows -- 4.2 Blocking Flows in Unit Capacity Graphs -- 4.3 The Goldberg-Rao Algorithm -- Exercises -- Chapter Notes -- Permissions -- 5 Minimum-Cost Circulation Algorithms -- 5.1 Optimality Conditions -- 5.2 Wallacher's Algorithm -- 5.3 Minimum-Mean Cycl…

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