文献类型：会议论文

英文题名：An Improved Quantum Evolutionary Algorithm and Its Application

作者：Ren Ailian[1];Zhou Liang;Qu Hongjian

第一作者：任爱莲

机构：[1]Henan Univ Finance & Econ, Sch Business Adm, Zhengzhou 450002, Henan, Peoples R China

第一机构：河南财经政法大学工商管理学院

会议论文集：3rd International Conference on Product Innovation Management

会议日期：OCT 25-26, 2008

会议地点：Wuhan, PEOPLES R CHINA

语种：英文

外文关键词：Quantum evolution algorithm; Clone; Mutation; Function optimization

摘要：When most of the quantum inspired evolution algorithms(QEA) are based on the genetic algorithm, then be improved and used for the optimization of continuous functions with multi-peak, However, they are easy to be trapped into the local deceptive peak. In this paper, a new improved quantum evolution algorithm is proposed to overcome the shortcoming of the above QEA. The new improved QEA combines the main mechanisms of clone. Experiments on test functions of diverse complexities are implemented and compared with other QEAs. The result indicates that the new algorithm in this paper can search and get the global optimum solution in a shorter time.