Transcription of Particle swarm optimization algorithm: an overview - kpfu.ru
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Particle swarm optimization algorithm: an overview - kpfu.ru
Soft ComputDOI swarm optimization algorithm: an overviewDongshu Wang1 Dapei Tan1 Lei Liu2 Springer-Verlag Berlin Heidelberg 2017 AbstractParticle swarm optimization (PSO) is apopulation-based stochastic optimization algorithm moti-vated by intelligent collective behavior of some animals suchas flocks of birds or schools of fish. Since presented in 1995, ithas experienced a multitude of enhancements. As researchershave learned about the technique, they derived new versionsaiming to different demands, developed new applications in ahostofareas,publishedtheoreticalstudies oftheeffectsofthevarious parameters and proposed many variants of the algo-rithm.
In studying the behavior of social animals with the artifi-cial life theory, for how to construct the swarm artificial life systems with cooperative behavior by computer, Millonas proposed five basic principles (van den Bergh 2001): (1) Proximity: the swarm should be able to carry out simple space and time computations.
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