文章基本信息

标题：Improved Multi-objective Genetic Algorithm Based on Parallel Hybrid Evolutionary Theory
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作者：Zou Yingyong ; Zhang Yongde ; Li Qinghua 等
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2015
卷号：8
期号：1
页码：133-140
DOI：10.14257/ijhit.2015.8.1.11
出版社：SERSC
摘要：Based on the analysis on the basic principles and characteristics of the existing multi- objective genetic algorithm (MOGA), an improved multi-objective GA with elites maintain is put forward based on non-dominated sorting genetic algorithm (NSGA). NSGA-II algorithm theory and parallel hybrid evolutionary theory is described in detail. The design principle, process and detailed implementations of the improved MOGA are given. IMNSGA-II algorithm and NSGA-II algorithm are applied to test the performance of the two algorithms for different test function, experiments of example are preformed. Experimental results show that the improved MOGA achieved the optimal between the convergence and diversity.
关键词：MOGA; parallel hybrid policy; elite-policy