Improved NSGA-II Algorithm for Optimization of Constrained Functions

被引：0
|
作者：
Zhang, Yun [1 ]
Jiao, Bin [1 ]
机构：
[1] Shanghai Dianji Univ, Shanghai, Peoples R China
来源：
PROCEEDINGS OF THE 2018 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL, AUTOMATION AND MECHANICAL ENGINEERING (EAME 2018) | 2018年 / 127卷
关键词：
multi-objective optimization; improved non-dominated sorting genetic algorithm; infeasible solutions; external save set;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In order to solve the constrained multi-objective optimization problem, an improved NSGA-II algorithm is proposed. On the basis of NSGA, the cross operation of the feasible and unfeasible solution is implemented in order to give full play to the role of the infeasible solution in the optimization process. In addition, the external preservation set is updated on the basis of the obtained dominant individual to preserve the optimal solution of the problem. The improved algorithm is applied to typical test functions and compared with NSGA-II. The experimental results show that the algorithm is superior.
引用
收藏
页码：316 / 319
页数：4
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