基于动态邻域的QPSO算法  

Quantum-behaved particle swarm optimization with neighbourhood operator

作　　者：孔丽丹[1] 须文波[1] 孙俊[1] 

机构地区：[1]江南大学信息工程学院,江苏无锡214122

出　　处：《计算机工程与应用》2008年第13期36-38,89,共4页Computer Engineering and Applications

基　　金：国家自然科学基金(the National Natural Science Foundation of China under Grant No.60474030)

摘　　要：为了保证种群的多样性,提高算法的全局搜索能力,在具有量子行为的粒子群优化算法(QPSO)中引入邻域拓扑结构的概念,采用邻域结构中的轮形结构,提出一种基于动态邻域的具有量子行为的粒子群优化算法(NQPSO)。并用若干个标准函数进行测试,比较了NQPSO算法与标准PSO(SPSO)和传统QPSO算法的性能。实验结果表明,NQPSO算法具有强的全局搜索能力,其性能优于其它两个算法,尤其体现在解决高维的优化问题上。In this paper,we introduce a concept of neighbourhood topology into the Quantum-behaved Panicle Swarm Optimization（QPSO） algorithm in order to ensure the diversity of the swarm and improve the algorithm＇s global search ability.We adopt the Wheel Topology and propose the Quantum-behaved Panicle Swarm Optimization with Neighbourhood Operator（NQPSO）. Finally,the performance of NQPSO algorithm is compared with those of Standard PSO （SPSO） and original QPSO by testing the algorithms on several benchmark functions.The experiments results show that NQPSO algorithm outperforms due to its strong global search ability,particularly in the optimization problems with high dimension.

关 键 词：粒子群优化 量子行为 邻域拓扑 轮形结构 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]