Fast algorithms for convex quadratic programming and multicommodity flows
STOC '86 Proceedings of the eighteenth annual ACM symposium on Theory of computing
A faster strongly polynomial minimum cost flow algorithm
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
The maximum concurrent flow problem
Journal of the ACM (JACM)
Finding minimum-cost circulations by successive approximation
Mathematics of Operations Research
A natural randomization strategy for multicommodity flow and related algorithms
Information Processing Letters
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Using separation algorithms in fixed dimension
Journal of Algorithms
Fast approximation algorithms for multicommodity flow problems
Selected papers of the 23rd annual ACM symposium on Theory of computing
Fast deterministic approximation for the multicommodity flow problem
Mathematical Programming: Series A and B
Optimization of Area Traffic Control for Equilibrium Network Flows
Transportation Science
| Hi-index | 0.01 |
The multi-commodity flow problem involves simultaneous shipping several different commodities from sources to sinks in a directed network with total amount of flow going through an edge limited by its capacity. The optimization version of the multi-commodity flow problem is the maximum concurrent flow problem, which finds a flow with the minimum congestion. For any positive ε, the ε-optimal concurrent flow problem is to find a solution whose the congestion value is no more than (1+ε) times the minimum congestion. In recent years, a few fast combinatorial approximation algorithms for the ε-optimal concurrent flow problem have been presented. In this paper we propose a new variant of the combinatorial approximation algorithm: CACF with a tighter computation bound in decreasing the values of congestion and the potential function. Numerical comparisons are made between the results obtained by the combinatorial approximation algorithms and those did by the linear programming package CPLEX on large-scale test networks. The application of CACF to efficiently solving the system-optimal network flow problem is given where good results have been obtained. It has shown the capacity of the CACF in dealing with problems of concurrent flow associated.