Particle swarm optimizer with adaptive species radius for multimodal function optimization

Based on species-PSO, this paper proposes an adaptive species radius strategy for multimodal function optimization. In species-PSO, The radius of the species is a very important parameter, which determines the success and failure of the algorithm. However, the value of the radius extremely depends on the corresponding optimization problems. The task of choosing an appropriate radius is difficult for users. We define stability of the species to denote the search ability for every species. According to stability of species and the number of members in species, the radius of the species is adjusted adaptively. The experimental results show that adaptive species radius strategy makes species-PSO could handle a wide range of optimization problems without user intervention and achieve good performance for multimodal function optimization.

[1]  Frans van den Bergh,et al.  A NICHING PARTICLE SWARM OPTIMIZER , 2002 .

[2]  Hyun-Kyo Jung,et al.  Niching genetic algorithm with restricted competition selection for multimodal function optimization , 1999 .

[3]  Tao Li,et al.  PSO with sharing for multimodal function optimization , 2003, International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003.

[4]  J. Kennedy,et al.  Stereotyping: improving particle swarm performance with cluster analysis , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[5]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[6]  Michael N. Vrahatis,et al.  On the computation of all global minimizers through particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[7]  David E. Goldberg,et al.  Genetic Algorithms with Sharing for Multimodalfunction Optimization , 1987, ICGA.

[8]  Xiaodong Li,et al.  Adaptively Choosing Neighbourhood Bests Using Species in a Particle Swarm Optimizer for Multimodal Function Optimization , 2004, GECCO.

[9]  P. John Clarkson,et al.  A Species Conserving Genetic Algorithm for Multimodal Function Optimization , 2002, Evolutionary Computation.

[10]  Samir W. Mahfoud.  Crowding and Preselection Revisited , 1992, PPSN.

[11]  Michael J. Shaw,et al.  Genetic algorithms with dynamic niche sharing for multimodal function optimization , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[12]  Ralph R. Martin,et al.  A Sequential Niche Technique for Multimodal Function Optimization , 1993, Evolutionary Computation.