Article ID Journal Published Year Pages File Type
4633989 Applied Mathematics and Computation 2008 12 Pages PDF
Abstract

Particle swarm optimization (PSO) as an efficient and powerful problem-solving strategy has been widely used, but appropriate adjustment of its parameters usually requires a lot of time and labor. So a co-evolving framework is proposed to improve the robustness of the PSO. In this paper, within this framework the fuzzy rules for the manipulation of the inertia weights are co-evolved with the particles. And the simulation results on a suite of test functions show that the use of this co-evolving framework improves the performance of the PSO, especially the robustness against the dimensional variation of the test functions.

Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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