文章基本信息

标题：An Improved Multi-objective Evolutionary Algorithm with the Hybrid Strategies
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作者：Gao Guibing ; Huang Gang ; Zhang Guojun 等
期刊名称：International Journal of Education and Management Engineering(IJEME)
印刷版ISSN：2305-3623
电子版ISSN：2305-8463
出版年度：2011
卷号：1
期号：3
页码：79-86
出版社：MECS Publisher
摘要：An improved multi-objective evolutionary algorithm with the hybrid strategies is presented in this paper for multi-objective optimization problems. The evolution process is divided into initial exploration stage, the middle feedback stage and the accelerating convergence stage by the amount of non-dominated individuals in the population. The hybrid strategies and adaptive population structure are employed to improve the behavior of the algorithm at the different stages. The proposed algorithm is validated by 3 benchmark test problems. Compared with three other famous multi-objective algorithms by two quality indicators, the proposed algorithm achieves competitive results.
关键词：Evolutionary algorithm; multi-objective optimization; hybrid; adaptive;non-dominated solution