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Network Flows and Matching: First DIMACS Implementation Challenge
Edited by: David S. Johnson and Catherine C. McGeoch
A co-publication of the AMS and DIMACS.
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DIMACS: Series in Discrete Mathematics and Theoretical Computer Science
1993; 592 pp; hardcover
Volume: 12
ISBN-10: 0-8218-6598-6
ISBN-13: 978-0-8218-6598-9
List Price: US$117
Member Price: US$93.60
Order Code: DIMACS/12
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Interest has grown recently in the application of computational and statistical tools to problems in the analysis of algorithms. In many algorithmic domains worst-case bounds are too pessimistic and tractable probabilistic models too unrealistic to provide meaningful predictions of practical algorithmic performance. Experimental approaches can provide knowledge where purely analytical methods fail and can provide insights to motivate and guide deeper analytical results. The DIMACS Implementation Challenge was organized to encourage experimental work in the area of network flows and matchings. Participants at sites in the U.S., Europe, and Japan undertook projects between November 1990 and August 1991 to test and evaluate algorithms for these problems. The Challenge culminated in a three-day workshop held in October 1991 at DIMACS. This volume contains the revised and refereed versions of twenty-two of the papers presented at the workshop, along with supplemental material about the Challenge and the Workshop.

Co-published with the Center for Discrete Mathematics and Theoretical Computer Science beginning with Volume 8. Volumes 1-7 were co-published with the Association for Computer Machinery (ACM).

Readership

Research mathematicians and computer scientists.

Table of Contents

  • R. J. Anderson and J. C. Setubal -- Goldberg's algorithm for maximum flow in perspective: A computational study
  • Q. C. Nguyen and V. Venkateswaran -- Implementations of the Goldberg-Tarjan maximum flow algorithm
  • T. Badics and E. Boros -- Implementing a maximum flow algorithm: Experiments with dynamic trees
  • F. Alizadeh and A. V. Goldberg -- Implementing the push-relabel method for the maximum flow problem on a connection machine
  • G. E. Shannon, J. MacCuish, and E. Johnson -- A case study in algorithm animation: Maximum flow algorithms
  • R. G. Bland, J. Cheriyan, D. L. Jensen, and L. Ladányi -- An empirical study of min cost flow algorithms
  • A. V. Goldberg and M. Kharitanov -- On implementing scaling push-relabel algorithms for the minimum-cost flow problem
  • I. Maros -- Performance evaluation of the MINET minimum cost netflow solver
  • S. Fujishige, K. Iwano, J. Nakano, and S. Tezuka -- A speculative contraction method for minimum cost flows: Toward a practical algorithm
  • S. T. McCormick and L. Liu -- An experimental implementation of the dual cancel and tighten algorithm for minimum-cost network flow
  • A. Joshi, A. S. Goldstein, and P. M. Vaidya -- A fast implementation of a path-following algorithm for maximizing a linear function over a network polytope
  • M. G. C. Resende and G. Veiga -- An efficient implementation of a network interior point method
  • S. Neilsen and S. Zenios -- On the massively parallel solution of linear network flow problems
  • J. M. Borger, T. S. Kang, and P. N. Klein -- Approximating concurrent flow with unit demands and capacities: An implementation
  • T. Leong, P. W. Shor, and C. Stein -- Implementation of a combinatorial multicommodity flow algorithm
  • D. A. Castañon -- Reverse auction algorithms for assignment problems
  • K. G. Ramakrishnan, N. K. Karmarkar, and A. P. Kamath -- An approximate dual projective algorithm for solving assignment problems
  • J. Hao and G. Kocur -- An implementation of a shortest augmenting path algorithm for the assignment problem
  • M. Brady, K. K. Jung, H. T. Nguyen, R. Raghavan, and R. Subramonian -- The assignment problem on parallel architectures
  • S. T. Crocker -- An experimental comparison of two maximum cardinality matching programs
  • R. B. Mattingly and N. P. Richey -- Implementing an \(O(\sqrt {N}M)\) cardinality matching algorithm
  • D. Applegate and W. Cook -- Solving large-scale matching problems
  • C. C. McGeoch -- Appendix A: Electronically available materials
  • D. S. Johnson -- Appendix B: Panel discussion highlights
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