Network Flow Algorithms

Inbunden, Engelska, 2019

AvDavid P. Williamson

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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 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.

Produktinformation

Utgivningsdatum2019-09-05
Mått157 x 235 x 22 mm
Vikt580 g
FormatInbunden
SpråkEngelska
Antal sidor326
FörlagCambridge University Press
ISBN9781107185890

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David P. Williamson is a Professor at Cornell University, New York, in the School of Operations Research and Information Engineering. He has won several awards for his work in discrete optimization, including the 2000 Fulkerson Prize, sponsored by the American Mathematical Society and the Mathematical Programming Society. His previous book, The Design of Approximation Algorithms (Cambridge, 2011), co-authored with David B. Shmoys, won the 2013 INFORMS Lanchester Prize. He has served on several editor boards, and was editor-in-chief of the SIAM Journal on Discrete Mathematics. He is a Fellow of the ACM and of SIAM.

'More than half a century since network flow theory was introduced by the 1962 book of L. R. Ford and D. R. Fulkerson, the area is still active and attractive. This book, based on course materials taught at Stanford and Cornell Universities, offers a concise and succinct description of most of the important topics, as well as covering recent developments. Its use in graduate courses related to algorithms and optimization is highly recommended.' Toshihide Ibaraki, Kyoto College of Graduate Studies for Informatics, Japan