Abstract
Hybrid particle swarm optimization (PSO) is such a kind of algorithms, which combine other algorithms or technologies to enhance the basic PSO. This paper compares three representative hybrid PSOs: breeding PSO, immune PSO, and chaos PSO. These comparisons are carried out in following aspects: the goals for hybrid, basic hybrid modes, the key implementation steps, optimization performances and so on. Through these comparisons and analysis, three hybrid algorithms' construction, implementation and respective application scope are summarized, especially, the optimization performances of three hybrid PSOs have been researched carefully. The goal is to find features of the three HPSOs and provide some guidence to develop new kinds of HPSO.
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