| 采用放松支配关系的高维多目标微分进化算法 |
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| 引用本文： | 申晓宁,孙 毅,薛云勇.采用放松支配关系的高维多目标微分进化算法[J].计算机工程与应用,2018,54(18):161-167. |
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| 作者姓名： | 申晓宁 孙 毅 薛云勇 |
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| 作者单位： | 南京信息工程大学 信息控制学院，南京 210044 |
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| 摘 要： | 为了提高进化算法在求解高维多目标优化问题时的收敛性和多样性，提出了采用放松支配关系的高维多目标微分进化算法。该算法采用放松的Pareto支配关系，以增加个体的选择压力；采用群体和外部存储器协同进化的方案，并通过混合微分变异算子，生成子代群体；采用基于指标的方法计算个体的适应度并对群体进行更新；采用基于Lp范数（0
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| 关 键 词： | 高维多目标优化 微分进化算法 放松支配 协同进化 变异 |
Differential evolution algorithm for many-objective using relaxed dominance relation |
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| SHEN Xiaoning,SUN Yi,XUE Yunyong.Differential evolution algorithm for many-objective using relaxed dominance relation[J].Computer Engineering and Applications,2018,54(18):161-167. |
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| Authors: | SHEN Xiaoning SUN Yi XUE Yunyong |
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| Affiliation: | School of Information Control, Nanjing University of Information Science and Technology, Nanjing 210044, China |
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| Abstract: | In order to improve the convergence and diversity of many-objective evolutionary algorithms, a many-objective differential evolution algorithm using a relaxed dominance relation is proposed. In the proposed algorithm, a relaxed domination relation is designed and incorporated to increase the selection pressure of individuals. Population is coevolved with an external archive, and the child population is generated by the mixed differential mutation operators. The fitness of each individual is evaluated based on an indicator method, and the population is updated. The archive is updated according to the Lp norm （0
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| Keywords: | many-objective optimization differential evolution algorithm relaxed dominance co-evolutionary mutation |
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