Abstract

Recently, Particle Swarm Optimization (PSO), gained vast attention and applied to variety of engineering optimization problems because of its simplicity and efficiency. The performance of the PSO algorithm can be further improved by hybrid techniques. There are numerous hybrid PSO algorithms published in the literature where researchers combine the benefits of PSO with other heuristic algorithms. In this paper, we propose a cooperative line search particle swarm optimization (CLS-PSO) algorithm by integrating local line search technique and standard PSO (S-PSO). The performance of the proposed hybrid algorithm, examined through six typical nonlinear optimization problems, is reported. Our experimental results show that CLS-PSO outperforms S-PSO.KeywordsPSOline searchhybrid algorithmnumerical experiments

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