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Proceedings ArticleDOI

A simple local-control approximation algorithm for multicommodity flow

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TLDR
A very simple (1+/spl epsi/)-approximation algorithm for the multicommodity flow problem that performs as well as or better than previously known algorithms, at least for certain test problems.
Abstract
In this paper, we describe a very simple (1+/spl epsi/)-approximation algorithm for the multicommodity flow problem. The algorithm runs in time that is polynomial in N (the number of nodes in the network) and /spl epsiv//sup -1/ (the closeness of the approximation to optimal). The algorithm is remarkable in that it is much simpler than all known polynomial time flow algorithms (including algorithms for the special case of one-commodity flow). In particular, the algorithm does not rely on augmenting paths, shortest paths, min-cost paths, or similar techniques to push flow through a network. In fact, no explicit attempt is ever made to push flow towards a sink during the algorithm. Because the algorithm is so simple, it can be applied to a variety of problems for which centralized decision making and flow planning is not possible. For example, the algorithm can be easily implemented with local control in a distributed network and it can be made tolerant to link failures. In addition, the algorithm appears to perform well in practice. Initial experiments using the DIMACS generator of test problems indicate that the algorithm performs as well as or better than previously known algorithms, at least for certain test problems. >

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References
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Proceedings ArticleDOI

An approximate max-flow min-cut theorem for uniform multicommodity flow problems with applications to approximation algorithms

TL;DR: The main result is an algorithm for performing the task provided that the capacity of each cut exceeds the demand across the cut by a Theta (log n) factor.
Journal ArticleDOI

Finding Minimum-Cost Circulations by Successive Approximation

TL;DR: This work develops a new approach to solving minimum-cost circulation problems that combines methods for solving the maximum flow problem with successive approximation techniques based on cost scaling and shows that a minimum- cost circulation can be computed by solving a sequence of On lognC blocking flow problems.
Proceedings ArticleDOI

Speeding-up linear programming using fast matrix multiplication

TL;DR: An algorithm for solving linear programming problems that requires O((m+n)/sup 1.5/nL) arithmetic operations in the worst case is presented, which improves on the best known time complexity for linear programming by about square root n.
Proceedings ArticleDOI

Fast approximation algorithms for multicommodity flow problems

TL;DR: It is proved that a (simple) k-commodity flow problem can be approximately solved by approximately solving O(k log2n) single-comodity minimum-cost flow problems, and the first polynomial-time combinatorial algorithms for approximately solving the multicommodation flow problem are described.
Proceedings ArticleDOI

Solving minimum-cost flow problems by successive approximation

TL;DR: This work introduces a framework for solving minimum-cost flow problems and shows how to extend techniques developed for the maximum flow problem to improve the quality of a solution.
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