哈尔滨工程大学学报2012，Vol.33Issue(8)：1022-1031,10.DOI:10.3969/j.issn.1006-7043.201205032
基于云差分进化算法的约束多目标优化实现
A cloud differential evolutionary algorithm for constrained multi-objective optimization
摘要
Abstract
Considering that the diversity and convergence of a constrained multi-objective optimization algorithm is not sufficient, a constrained multi-objective optimization algorithm based on a cloud differential evolutionary algorithm was proposed in this paper. First, parameter CR was adjusted adaptively based on a cloud model. Secondly, constraint conditions were considered by utilizing external population to store feasible and unfeasible solutions, and the updating method of the feasible solution set was improved to increase distribution. Finally, a novel mutation strategy was proposed which enhanced the exploration ability of the algorithm by utilizing direction information of excellent feasible and unfeasible solutions. The simulation results of CTP standard test functions show that the constrained multi-objective optimization algorithm in this paper outperforms the other two state-of-the-art constraint multi-objective evolutionary algorithms in terms of diversity metrics and is closer to the true front of Pareto, which proves the superiority of this algorithm in solving constraint multi-objective optimal problems.关键词
约束多目标优化/差分进化算法/云模型/变异策略Key words
constrained multi-objective optimization/ differential evolutionary algorithm/ cloud model/ mutation strategy分类
信息技术与安全科学引用本文复制引用
毕晓君,刘国安..基于云差分进化算法的约束多目标优化实现[J].哈尔滨工程大学学报,2012,33(8):1022-1031,10.基金项目
国家自然科学基金资助项目(61175126) （61175126）
中央高校基本科研业务费专项资金资助项目(HEUCFZ1209) （HEUCFZ1209）
教育部博士点基金资助项目(20112304110009). （20112304110009）
