论文信息 - Particle Swarm Optimization: efficient globally convergent modifications

Particle Swarm Optimization: efficient globally convergent modifications

In this paper we consider the Particle Swarm Optimization (PSO) algorithm [1], [2], in the class of Evolutionary Algorithms, for the solution of global optimization problems. We analyze a couple of issues aiming at improving both the effectiveness and the efficiency of PSO. In particular, first we recognize that in accordance with the results in [3], the initial points configuration required by the method, may be a crucial issue for the efficiency of PSO iteration. Therefore, a promising strategy to generate initial points is provided in the paper.

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