Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
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In this paper, a new variation of Particle Swarm Optimization (PSO) based on hybridization with Reduced Variable Neighborhood Search (RVNS) is proposed. In our method, general flow of PSO is preserved. However, to rectify premature convergence problem of PSO and to improve its exploration capability, the best particle in the swarm is randomly re-initiated. To enhance exploitation mechanism, RVNS is employed as a local search method for these particles. Experimental results on standard benchmark problems show sign of considerable improvement over the standard PSO algorithm.