西北师范大学学报（自然科学版）2018，Vol.54Issue(3)：40-46,7.DOI:10.16783/j.cnki.nwnuz.2018.03.008
动态参数调整的多策略差分进化算法
Multi-strategy differential evolutionary algorithm for dynamic parameter adjustment
摘要
Abstract
In order to solve the problem of slow convergence and premature convergence in the differential evolution algorithm in the process of function optimization problems,a multi-strategy differential evolutionary algorithm for dynamic parameter adjustment(MDADE)is proposed.At the beginning of optimization,the population is randomly divided into three independent subpopulations.The algorithm adopts three different mutation strategies to ensure the diversity of the population.The convergence performance of the algorithm is improved by the parameter adaptive mechanism.After a certain algebraic evolution,the algorithm is simulated by 25 standard test functions of CEC2005.The experimental results show that the new algorithm can effectively avoid premature convergence and has better optimization performance.关键词
差分进化/择优保留/参数自适应/多策略/CEC2005Key words
differential evolution/elitist reservation/parameter adaptive/multi-strategy/CEC2005分类
信息技术与安全科学引用本文复制引用
马永杰,朱琳,田福泽..动态参数调整的多策略差分进化算法[J].西北师范大学学报（自然科学版）,2018,54(3):40-46,7.基金项目
国家自然科学基金资助项目(41461078) （41461078）
