A review of particle swarm optimization. Part I: background and development
Natural Computing: an international journal
Natural Computing: an international journal
Fast multi-swarm optimization with cauchy mutation and crossover operation
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
A new hybrid algorithm of particle swarm optimization
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
Mobile robot navigation using particle swarm optimization and adaptive NN
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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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.