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Trans. Planning Journal

Title A PATH-BASED ANALOGOUS PARTICLE SWARM OPTIMIZATION ALGORITHM FOR MINIMUM COST NETWORK FLOW PROBLEMS WITH CONCAVE ARC COSTS
Author Shangyao Yan, Wang-Tsang Lee, Yu-Lin Shih
Summary   In this research, a particle swarm optimization algorithm was employed, coupled with the techniques of a genetic algorithm, and threshold acceptance method and concave cost network heuristics, to develop a path-based global search algorithm for efficiently solving minimum cost network flow problems with square root concave arc costs. To evaluate the proposed algorithm, several network flow problems are randomly generated. C++ is used to code all the necessary programs for the tests. The results indicate that the proposed algorithm is more effective than recently designed local search algorithms and genetic algorithms for solving minimum cost network flow problems with square root concave arc costs.
Vol. 36
No. 3
Page 393
Year 2007
Month 9
Count Views:434
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