Self-adapting Scalable Differential Evolution Algorithm

作     者：刘荣辉 郑建国 

作者机构：Department of Computer Science and EngineeringHenan University of Urban Construction Glorious Sun School of Business and ManagementDonghua University 

出 版 物：《Journal of Donghua University(English Edition)》 (东华大学学报（英文版）)

年 卷 期：2011年第28卷第4期

页      面：384-390页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China (No. 70971020) 

主　　题：differential evolution (DE) scalable self-adapting parameter control function optimization 

摘      要：Differential evolution(DE) demonstrates good convergence performance,but it is difficult to choose trial vector generation strategies and associated control parameter *** improved method,self-adapting scalable DE(SSDE) algorithm,is *** vector generation strategies and crossover probability are respectively self-adapted by two operators in this ***,to enhance the convergence rate,vectors selected randomly with the optimal fitness values are introduced to guide searching *** problems are used to verify this *** with other well-known DE algorithms,experiment results indicate that this algorithm is better than other DE algorithms in terms of convergence rate and quality of optimization.