Design of Population Size for Multi-objective Particle Swarm Optimization Algorithm Based on the Convergence Speed and Diversity
HAN Hong-gui1,2, WU Shu-jun1,2
1. Department of Information, Beijing University of Technology, Beijing 100124, China;
2. Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China
Abstract:To determine the population size of multi-objective particle swarm optimization algorithm (MOPSO),an improved MOPSO,based on the convergence speed and diversity,named CD-MOPSO,is proposed.Firstly,the fitness function of population size,which is developed by the convergence speed and diversity during the evolutionary process,is used to describe the relationship between the population size and the performance of MOPSO.Secondly,according to the fitness function,an adaptive adjustment method is designed to update the population size of MOPSO dynamically.Finally,the proposed CD-MOPSO is tested on the ZDT benchmark optimization problems and applied to a real optimization problem of urban pipe networks.The experimental results show that the proposed CD-MOPSO can adjust the population size automatically according to the problem,compared with the performance of NSGA,MOPSO,SPEA2 and EMDS-MOPSO,CD-MOPSO has faster convergence speed with better optimization results.
韩红桂, 武淑君. 基于收敛速度和多样性的多目标粒子群种群规模优化设计[J]. 电子学报, 2018, 46(9): 2263-2269.
HAN Hong-gui, WU Shu-jun. Design of Population Size for Multi-objective Particle Swarm Optimization Algorithm Based on the Convergence Speed and Diversity. Acta Electronica Sinica, 2018, 46(9): 2263-2269.
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