文献类型：会议论文

英文题名：Studying the performance of quantum evolutionary algorithm based on immune theory

作者：You, Xiaoming[1,2];Liu, Sheng[1,2];Shuai, Dianxun[2]

机构：[1]Shanghai Univ Engn Sci, Coll Elect & Elect Engn, Shanghai 200065, Peoples R China;[2]East China Univ Sci & Technol, Dept Comp Sci & Technol, Shanghai 200237, Peoples R China

会议论文集：7th International Conference on Computational Science (ICCS 2007)

会议日期：MAY 27-30, 2007

会议地点：Beijing, PEOPLES R CHINA

语种：英文

外文关键词：quantum evolutionary algorithm; immune theory; self-adaptive mutation; cross-mutation; performance

摘要：A novel quantum evolutionary algorithm based on immune operator (MQEA) is proposed. The algorithm can find out optimal solution by the mechanism in which antibody can be clone selected, immune cell can accomplish cross-mutation and Self-adaptive mutation, memory cells can be produced and similar antibodies can be suppressed. It not only can maintain quite nicely the population diversity than the classical evolutionary algorithm, but also can help to accelerate the convergence speed. The technique for improving the performance of MQEA has been described and its superiority is shown by some simulation experiments in this paper.