A Multi-objective optimal evolutionary algorithm based on tree-ranking |
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Authors: | Shi Chuan Kang Li-shan Li Yan Yan Zhen-yu |
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Affiliation: | (1) State Key Laboratory of Software Engineering, Wuhan University, 430072 Wuhan, Hubei, China |
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Abstract: | 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 shortcomings, 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. Foundation item: Supported by the National Natural Science Foundation of China(60073043, 70071042, 60133010) Biography: Shi Chuan( 1978-), male, Master candidate, research direction; intellective computation, evolutionary computation. |
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Keywords: | multi-objective optimal problem multi-objective optimal evolutionary algorithm Pareto dominance tree structure dynamic space-compressed mutative operator |
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