Abstract
Inspired by the phenomenon of symbiosis in natural ecosystem, a master-slave mode is incorporated into Particle Swarm Optimization (PSO), and a Multi-population Cooperative Optimization (MCPSO) is thus presented. In MCPSO, the population consists of one master swarm and several slave swarms. The slave swarms execute PSO (or its variants) independently to maintain the diversity of particles, while the master swarm enhances its particles based on its own knowledge and also the knowledge of the particles in the slave swarms. In the simulation part, several benchmark functions are performed, and the performance of the proposed algorithm is compared to the standard PSO (SPSO) to demonstrate its efficiency.
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Niu, B., Zhu, Y., He, X. (2005). Multi-population Cooperative Particle Swarm Optimization. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_88
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DOI: https://doi.org/10.1007/11553090_88
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