期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：3
页码：125-132
DOI：10.14257/ijhit.2016.9.3.12
出版社：SERSC
摘要：In this paper, chaos theory and the traditional multi-objective optimization evolutionary algorithm is put forward, "Chaos-based multi-objective evolutionary algorithm", combines a variety of optimization strategies. The traditional multi-objective evolutionary algorithm for repeating individual causes of variation is based on chaotic analysis of multi-objective evolutionary algorithm and demonstration. According to the characteristics of chaotic map tent, NSGA-II algorithm in this paper on the basis of chaotic map was proposed based on chaotic tent initialization and chaotic mutation multi-objective evolutionary algorithm. The original NSGA-II algorithm is improved, and the introduction of adaptive mutation operator and a new crowding distance is calculated and applied to the design of the algorithm. Analysis and experimental results show that these methods can better improve the distribution of population performance.
