| 基于聚集密度的协同进化多目标优化算法 |
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| 引用本文： | 吴福芳,许峰.基于聚集密度的协同进化多目标优化算法[J].人天科学研究,2014(11):39-42. |
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| 作者姓名： | 吴福芳 许峰 |
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| 作者单位： | 安徽理工大学理学院,安徽淮南232001 |
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| 基金项目： | 安徽省教育厅自然科学基金项目（2013kb236） |
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| 摘 要： | 为了改善协同进化多目标优化算法性能，引入了聚集密度对超级个体集合进行更新。其基本思想是：首先计算种群中各个体的聚集密度，再定义一个偏序集，然后根据一定的比例依次从偏序集中选择个体更新。根据数值试验和量化指标测试了新算法的收敛性与分布性。结果表明，新算法在收敛性方面与常规协同进化多目标算法相当，但其分布性获得了一定程度的改善。
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| 关 键 词： | 多目标优化 协同进化 聚集密度 分布性 |
The Co-evolutionary Multi-objective Optimization Algorithm Based on Crowding-density |
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| Abstract: | In order to improve the performance of co-evolutionary multi-objective optimization algorithm ,the crowding-density is put into to algorithm for updating the super individual collection .The basic idea is：First ,the crowding-density of each individual in the group is calculated ,and then a partial order set is set up according to the objective function value and crowding-density .Finally ,individuals are selected from the partial order set according to the principle of proportional selection ,and the elite set is updated .The convergence and distribution of improved algorithm are studied by means of nu-merical experiments ,and results show that ：The convergence of improved algorithm is roughly equal with the conventional co-evolutionary multi-objective optimization algorithm ,but the distribution of improved algorithm has been significantly improved . |
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| Keywords: | Multi-objective Optimization Co-evolution Crowding-density Distribution |
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