计算机工程与应用2019，Vol.55Issue(9)：49-55,7.DOI:10.3778/j.issn.1002-8331.1808-0028
基于变异算子和邻域值自适应的MOEA/D算法
Improved MOEA/D Algorithm Based on Adaptive Mutation Operator and Neighborhood Size
摘要
Abstract
When solving multiobjective problems, Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D)is simple and effective. But most MOEA/D use fixed control parameters. It will lead to poor ability of global search and make it difficult to balance convergence and diversity. To solve these problems, a multiobjective optimization algorithm based on adaptive mutation operator and neighborhood value is proposed in this paper. The algorithm adjusts the mutation operator adaptively based on the degree of dispersion or concentration of individual fitness values in the population. It can enhance the global search ability of the algorithm. The size of neighborhood is adjusted adaptively according to the stages of evolution and the degree of concentration of individual fitness values. Each individual has a neighborhood size in each generation. The number of individuals are counted, which dominate the individual corresponding to the subproblem in the neighborhood of subproblem. If this number exceeds the set upper limit, the Pareto dominance relationship will be also used as one of the criteria for judging the individual quality in the neighborhood. The proposed algorithm is compared with traditional MOEA/D in the standard test problem. The result shows that the solution set obtained by the proposed algorithm not only has better convergence and diversity, but also has a competitive performance in solving multiobjective problems.关键词
自适应/变异算子/邻域值/支配关系/多目标Key words
adaptive/ mutation operator/ neighborhood size/ domination relationship/ multiobjective分类
信息技术与安全科学引用本文复制引用
李二超,陈瑞婷..基于变异算子和邻域值自适应的MOEA/D算法[J].计算机工程与应用,2019,55(9):49-55,7.基金项目
国家自然科学基金地区基金(No.61763026) （No.61763026）
国家自然科学基金青年基金(No.61403175). （No.61403175）
