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A co-evolving framework for robust particle swarm optimization
- Source :
-
Applied Mathematics & Computation . Jun2008, Vol. 199 Issue 2, p611-622. 12p. - Publication Year :
- 2008
-
Abstract
- 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. [Copyright &y& Elsevier]
- Subjects :
- *ALGORITHMS
*MATHEMATICAL optimization
*MATHEMATICS
*MATHEMATICAL analysis
Subjects
Details
- Language :
- English
- ISSN :
- 00963003
- Volume :
- 199
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Applied Mathematics & Computation
- Publication Type :
- Academic Journal
- Accession number :
- 31919754
- Full Text :
- https://doi.org/10.1016/j.amc.2007.10.017