A co-evolving framework for robust particle swarm optimization

作者：Luo, Qiang^*; Yi, Dongyun

来源：Applied Mathematics and Computation, 2008, 199(2): 611-622.

DOI：10.1016/j.amc.2007.10.017

• particle swarm optimization
• evolutionary algorithm
• numerical optimization
• fuzzy logical controller
• analysis of algorithms

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.

• 出版日期2008-6-1
• 单位中国人民解放军国防科学技术大学