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Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm. (English) Zbl 1184.68621
Summary: This letter presents a formal stochastic convergence analysis of the standard particle swarm optimization (PSO) algorithm, which involves with randomness. By regarding each particle’s position on each evolutionary step as a stochastic vector, the standard PSO algorithm determined by non-negative real parameter tuple {ω,c 1 ,c 2 } is analyzed using stochastic process theory. The stochastic convergent condition of the particle swarm system and corresponding parameter selection guidelines are derived.
MSC:
68W20Randomized algorithms