Computer Science ›› 2015, Vol. 42 ›› Issue (8): 249-252.

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Dynamic Multi-objective Particle Swarm Optimization Algorithm Based on Human Social Behavior

WU Da-qing, ZHENG Jian-guo, ZHU Jia-jun and SUN Li   

  • Online:2018-11-14 Published:2018-11-14

Abstract: In order to improve the processing performance of the multi-objective optimization problem,reduce the computational complexity and improve the convergence of the algorithm,a multi-objective particle swarm optimization algorithm based on a human social behavior was proposed.The strategies such as promotion/resistance factor and the local jump strategy are introduced in proposed algorithm,to make the algorithm have strong global search ability and good robust performance.Some typical multi-objective optimization functions were tested to verify the algorithm.The results show that the proposed algorithm has superior performance of fast convergence speed and strong ability to jump out of local optimum,so it can be used for many fields.

Key words: Multi-objective optimization algorithm,Elite particle,Mediocrity particle,Local jump strategy

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