关键词: 量子粒子群算法, 人工蜂群搜索算子, 双中心粒子

Abstract: For the Quantum Particle Swarm Optimization algorithm based on artificial colony search operator（IQPSO） precision is not ideal and slow convergence speed, this paper combines a new strategy of updating the global optimal with IQPSO algorithm, introduces double center particle and makes the global optimum solutions for each dimension which are replaced with double center particle dimension corresponding respectively to update the global optimum again, near the algorithm solution to explore more accurate results. Through the five test functions compared with IQPSO algorithm, simulation experiments validate the proposed algorithm has better accuracy and faster convergence speed.

Key words: Quantum Particle Swarm Optimization（QPSO） algorithm, arti?cial bee colony search operator, double-center particle