文章基本信息

标题：An Improved Nonlinear Multi-Objective Optimization Problem Based on Genetic Algorithm
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作者：Yali Yun ; Yaping Li
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：7
页码：361-372
DOI：10.14257/ijhit.2016.9.7.33
出版社：SERSC
摘要：Genetic algorithms for multi-objective optimization problem to be solved were studied. Through the elitist strategy analysis, it is an improved multi-objective optimization algorithm. The algorithm uses a data warehouse to store the optimal solution produced by individuals in each generation, from the way individuals adopt measures to phase out the individual data warehouse identical or similar, the algorithm also improved selection operator, so that the algorithm adaptive capacity enhancement, the new algorithm improves the algorithm performance, improves the quality of understanding between sets, can get a lot of optimal and balanced.
关键词：genetic algorithm; multi-objective optimization; optimal solutions; ; crossover; mutation