A Family Particle Swarm Optimization Based on the Animal Collective Behavior

Abstract:

To study the organizational structure of particles in particle swarm optimization (PSO), we have proposed the family PSO (FPSO) previously. To further study the internal structure of FPSO, this paper introduced the animal collective behavior into the FPSO. It made the interaction ruling among particles was not based on random selection but topological distance. Each family interacted on average with a fixed number of neighbors, rather than with all neighbors within a fixed metric distance. Simulations for four benchmark functions demonstrated that the interaction ruling based on topological distance among particles was more reasonable than that on random selection.

• Periodical: Applied Mechanics and Materials (Volumes 513-517)
• Pages: 2439-2443
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.513-517.2439
• Online since: February 2014
• Authors: Zhen Zhou An*, Jin Rong Bai, Yu Ma, Na Yu Jia, Xin Ling Shi
• Keywords: Animal Collective Behavior, Family, Particle Swarm Optimization (PSO)

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