关键词: 粒子群算法, 量子行为, 自我更新机制, 多样性, 全局收敛, 老化

Abstract: Life body has limited life in nature；it will be aging and die with time. The aging mechanism is very important to keep swarm diversity during evolutionary process. For the phenomenon that Quantum-behaved Particle Swarm Optimization（QPSO） is often premature convergence, self-renewal mechanism is proposed into QPSO, and a leading particle and challengers are introduced. When the leading power of leading particle is exhausted, one challenger will select to be the new leading particle and continues keeping the diversity of swarm with a certain renewal mechanism. Furthermore, global convergence of the proposed algorithm is proved. Finally, the comparison and analysis of results with the proposed method and classical improved QPSO algorithm based on twelve CEC2005 benchmark function is given, the simulation results show stronger global searching ability of the modified algorithm. Especially in the seven multi-model test functions, the comprehensive performance is optimal.

Key words: PSO algorithm, quantum behaved, self-renewal mechanism, diversity, global convergence, aging