计算机工程与应用2016，Vol.52Issue(15)：29-33,5.DOI:10.3778/j.issn.1002-8331.1409-0268
引入人工蜂群搜索算子的QPSO算法的改进实现
Realization of improved Quantum Particle Swarm Optimization algo-rithm based on search operator of artificial bee colony
摘要
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.关键词
量子粒子群算法/人工蜂群搜索算子/双中心粒子Key words
Quantum Particle Swarm Optimization(QPSO)algorithm/artificial bee colony search operator/double-center particle分类
信息技术与安全科学引用本文复制引用
苑帅,沈西挺,邵娜娜..引入人工蜂群搜索算子的QPSO算法的改进实现[J].计算机工程与应用,2016,52(15):29-33,5.基金项目
天津市基金/市科委重点资助项目（No.14JCZDJC31600）。 （）
