Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (21): 142-144.DOI: 10.3778/j.issn.1002-8331.2008.21.039

• 机器学习 • Previous Articles     Next Articles

Immune quantum evolutionary algorithm based on chaos theory

LIU Sheng,YOU Xiao-ming   

  1. School of Management,Shanghai University of Engineering Science,Shanghai 200065,China
  • Received:2008-04-30 Revised:2008-06-02 Online:2008-07-21 Published:2008-07-21
  • Contact: LIU Sheng

基于混沌理论的免疫量子进化算法

刘 升,游晓明   

  1. 上海工程技术大学 管理学院,上海 200065
  • 通讯作者: 刘 升

Abstract: A novel immune quantum evolutionary algorithm based on chaos theory(CIQEA) is proposed.By chaos theory and niche methods population is divided into subpopulations of real-coded chromosome automatically,and then local search is carried by the immune mechanism,each subpopulation can obtain optimal solution.Chaos search is capable of escaping from premature.We introduce real-coded chromosome to solve precision and efficiency problem of binary system.The quantum evolutionary algorithm with intrinsic parallelism is integrated with adaptive immune dynamic model,it not only can maintain quite nicely the population diversity than the classical evolutionary algorithm,but also can help to accelerate the convergence speed and has able to get the global optimal and sub-optimal solutions rapidly.Its superiority is shown by some simulation experiments in this paper.

Key words: immune quantum evolutionary algorithm, chaos theory, cross and mutation

摘要: 提出了基于混沌理论的免疫量子进化算法,该算法应用混沌理论并依据小生境机制将初始个体划分为实数编码染色体的子群,各子群应用免疫特性的局域搜索能力找出优化解。混沌优化搜索机制能有效避免早熟收敛。为解决2进制算法所不能避免的精度与效率的冲突,采用10进制编码染色体。算法综合了量子计算的天然并行性、免疫算法的充分自适应性和混沌系统的遍历性,它比传统的进化算法具有更好的种群多样性,更快的收敛速度,更有效的全局和局域寻优能力。仿真实验也表明了该算法的优越性。

关键词: 免疫量子进化算法, 混沌理论, 交叉和变异