摘要

In this paper, a new particle swarm algorithm based on harmony search (PSO-HS) is presented to solve complex optimization problems. The key to this algorithm lies in combining the standard PSO algorithm and harmony search algorithm to achieve faster convergence and better accuracy of final solution without getting trapped in local minima. The PSO-HS has comprehensively been evaluated on 6 benchmark functions with different dimensions, different population size, and different characteristics such as unimodal, multimodal. Results show that PSO-HS substantially enhances the performance of the PSO when compared with three other variants of the PSO.

  • 出版日期2012

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