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A Multi-Objective Optimal Evolutionary Algorithm Based on Tree-Ranking 被引量:1
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作者 Shi Chuan, Kang Li-shan, Li Yan, Yan Zhen-yuState Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei,China 《Wuhan University Journal of Natural Sciences》 CAS 2003年第S1期207-211,共5页
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 so... 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. 展开更多
关键词 multi-objective optimal problem multi-objective optimal evolutionary algorithm Pareto dominance tree structure dynamic space-compressed mutative operator
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