| 一种用于多目标约束优化的改进进化算法 |
| |
| 引用本文： | 俞国燕,李鹏,何真,孙延明.一种用于多目标约束优化的改进进化算法[J].计算机集成制造系统,2009,15(6). |
| |
| 作者姓名： | 俞国燕 李鹏 何真 孙延明 |
| |
| 作者单位： | 1. 广东海洋大学工程学院,广东,湛江,524025
2. 华南理工大学,工商管理学院,广东,广州,510640 |
| |
| 基金项目： | 国家自然科学基金，广东省海洋渔业局资助项目 |
| |
| 摘 要： | 当前求解多目标优化的进化算法主要考虑如何处理相互冲突的多个目标间的优化,很少考虑对约束条件处理的问题.对此,给出了一种基于双群体搜索机制的改进差分进化算法,以求解多目标约束优化问题.采用两个不同种群,分别保存可行个体与不可行个体的双群体约束处理策略,利用基于Pareto的分类排序多目标优化技术,完成对进化个体解的评价.并通过群体混沌初始化、自适应交叉和变异操作来提高基本差分进化算法的性能.对三个经典测试函数的仿真结果表明,文中算法在均匀性、逼近性及收敛速度三方面均优于非支配排序遗传算法,而收敛速度也优于另两种改进进化算法.
|
| 关 键 词： | 差分进化 约束优化 多目标优化 仿真 |
Advanced evolutionary algorithm used in multi-objective constrained optimization problem |
| |
| YU Guo-yan,LI Peng,HE Zhen,SUN Yan-ming.Advanced evolutionary algorithm used in multi-objective constrained optimization problem[J].Computer Integrated Manufacturing Systems,2009,15(6). |
| |
| Authors: | YU Guo-yan LI Peng HE Zhen SUN Yan-ming |
| |
| Affiliation: | 1.Engineering College;Guangdong Ocean University;Zhanjiang 524025;China;2.School of Business Administration;South China University of Technology;Guangzhou 510640;China |
| |
| Abstract: | Evolutionary algorithm for constrained multi-objective optimization problems mainly focused on how to deal with conflicts among multi-objectives,while little consideration was given on how to deal with constraint condition.To deal with this problem,based on double populations searching scheme,an improved differential evolution algorithm was proposed for multi-objective constraint optimization problem.Two different populations were adopted to preserve constraints in optimization process,one was feasible solu... |
| |
| Keywords: | differential evolution constrained optimization multi-objective optimizationl simulation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
