计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (23): 57-60.

• 研究、探讨 • 上一篇    下一篇

一种基于相位编码的自适应量子粒子群算法

李盼池,张巧翠,杨 雨   

  1. 大庆石油学院 计算机与信息技术学院,黑龙江 大庆 163318
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-08-11 发布日期:2011-08-11

Adaptive quantum particle swarm algorithm based on phase encoding

LI Panchi,ZHANG Qiaocui,YANG Yu   

  1. School of Computer & Information Technology,Daqing Petroleum Institute,Daqing,Heilongjiang 163318,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-08-11 Published:2011-08-11

摘要: 为提高粒子群算法的优化性能,提出了一种基于相位编码的量子粒子群算法。用量子比特的相位描述粒子的空间位置,用Pauli-Z门实现粒子位置的变异。通过研究惯性因子、自身因子和全局因子的关系,提出了全局因子的自适应确定方法。以典型函数的极值优化和样本聚类问题为例的实验结果表明,该方法明显优于普通粒子群算法。

关键词: 粒子群优化, 相位编码, 自适应调整, 优化算法

Abstract: To improve the performance of particle swarm optimization,an adaptive quantum particle swarm optimization algorithm is proposed.In proposed algorithm,the position of particles is described by the phase of quantum bits,and the position mutation of particles is achieved by Pauli-Z gates.By studying the relationship among inertia factors,self-factors and global-
factors,an adaptive determination of the global-factors is proposed.Taking function extremum optimizing and samples clustering for example,the experimental results show that the proposed algorithm is obviously superior to the standard particle swarm optimization.

Key words: particle swarm optimization, phase encoding, adaptive adjustment, optimization algorithm