Solving A Kind of High Complexity Multi-Objective Problems by A Fast Algorithm

作     者：Zeng San-you, Ding Li-xin, Kang Li-shanDepartment of Computer Science,China University of GeoSciences, Wuhan 430074, Hubei, China Department of Computer Science, Zhuzhou Institute of Technology , Zhuzhou 412008, Hunan, China State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei, China 

作者机构：Department of Computer Science China University of GeoSciences Wuhan Hubei China Department of Computer Science Zhuzhou Institute of Technology Zhuzhou Hunan China State Key Laboratory of Software Engineering Wuhan University Wuhan Hubei China 

出 版 物：《Wuhan University Journal of Natural Sciences》 (武汉大学学报（自然科学英文版）)

年 卷 期：2003年第8卷第S1期

页      面：183-188页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

基　　金：Supported by the National Natural Science Foundation of China(60204001 70071042 60073043 60133010)and Youth Chengguang Project of Science and Technology of Wuhan City(20025001002) 

主　　题：evolutionary algorithms orthogonal design multi-objective optimization Pareto-optimal set 

摘      要：A fast algorithm is proposed to solve a kind of high complexity multi-objective problems in this paper. It takes advantages of both the orthogonal design method to search evenly, and the statistical optimal method to speed up the computation. It is very suitable for solving high complexity problems, and quickly yields solutions which converge to the Pareto-optimal set with high precision and uniform distribution. Some complicated multi-objective problems are solved by the algorithm and the results show that the algorithm is not only fast but also superior to other MOGAS and MOEAs, such as the currently efficient algorithm SPEA, in terms of the precision, quantity and distribution of solutions.