A Multi-Objective Optimal Evolutionary Algorithm Based on Tree-Ranking  

作　　者：Shi Chuan, Kang Li-shan, Li Yan, Yan Zhen-yuState Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei,China 

出　　处：《Wuhan University Journal of Natural Sciences》2003年第S1期207-211,共5页武汉大学学报（自然科学英文版）

基　　金：Supported by the National Natural Science Foundation of China(60073043,70071042,60133010)

摘　　要：Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has some shortcoming s, in this paper, we proposed a new method using tree structure to express the relationship of solutions. Experiments prove that the method can reach the Pare-to front, retain the diversity of the population, and use less time.Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has some shortcoming s, in this paper, we proposed a new method using tree structure to express the relationship of solutions. Experiments prove that the method can reach the Pare-to front, retain the diversity of the population, and use less time.

关 键 词：multi-objective optimal problem multi-objective optimal evolutionary algorithm Pareto dominance tree structure dynamic space-compressed mutative operator 

分 类 号：O224[理学—运筹学与控制论]