Stereotyping: improving particle swarm performance with cluster analysis

Individuals in the particle swarm population were "stereotyped" by cluster analysis of their previous best positions. The cluster centers then were substituted for the individuals' and neighbors' best previous positions in the algorithm. The experiments, which were inspired by the social-psychological metaphor of social stereotyping, found that performance could be generally improved by substituting individuals', but not neighbors', cluster centers for their previous bests.

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