Fast approximation algorithms for multicommodity flow problems:

Abstract: "All previously known algorithms for solving the multicommodity flow problem with capacities are based on linear programming. The best of these algorithms [14] uses a fast matrix multiplication algorithm and takes [formula] time to find an approximate solution, where k is the number o...

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Gespeichert in:
Bibliographische Detailangaben
Format: Buch
Sprache:English
Veröffentlicht: Stanford, Calif. 1991
Schriftenreihe:Stanford University / Computer Science Department: Report STAN-CS 1375
Schlagworte:
Zusammenfassung:Abstract: "All previously known algorithms for solving the multicommodity flow problem with capacities are based on linear programming. The best of these algorithms [14] uses a fast matrix multiplication algorithm and takes [formula] time to find an approximate solution, where k is the number of commodities, n and m denote the number of nodes and edges in the network, D is the largest demand, and U is the largest edge capacity. Substantially more time is needed to find an exact solution. As a consequence, even multicommodity flow problems with just a few commodities are believed to be much harder than single-commodity maximum-flow or minimum-cost flow problems.
Beschreibung:25 S.

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