Abstract

Based on the refinement successes to particle swarm optimization (PSO) methods, which include, namely, the introduction of an age variable, the proposal of new selection strategies to find the best solutions of the particle as well as for its neighbors, the design of a novel formula for velocity updating, the incorporation of an intensification search phase, and so on, an improved PSO method is presented. The experimental results reported indicate that the refined pinpointing search ability and the global search ability of the proposed method are significantly improved when compared to those of conventional PSOs

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