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A more efficient pre-initializing strategy of PSO algorithm: Multi-Period Particle Swarm Optimization (MP-PSO) is proposed. The process is divided into two periods: pre-initialization and post-optimization. The former is determined to find a better local solution to initialize the next period instead of standard uniform randomness. In order to explore further, adaptive escaping weight is adopted to...
In this paper, a new memetic algorithm, which combines PSO and local search technique, is proposed for mul-timodal optimization problems. In the investigated algorithm, a local PSO model is used to disperse the individuals into different sub-regions, an adaptive local search method is employed to refine the quality of individuals and a triggered re-initialization scheme is introduced to enhance the...
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