A genetic algorithm for solving multi-constrained function optimization problems based on KS function

被引：12
|
作者：
Xiao, Jianhua [1 ]
Xu, Jin [1 ]
Shao, Zehui [1 ]
Jiang, Congfeng [2 ]
Pan, Linqiang [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Dept Control Sci & Engn, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China
来源：
2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS | 2007年
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1109/CEC.2007.4425060
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a new genetic algorithm for solving multi-constrained optimization problems based on KS function is proposed. Firstly, utilizing the agglomeration features of KS function, all constraints of optimization problems are agglomerated to only one constraint. Then, we use genetic aligorithm to solve the optimization problem after the compression of constraints. Finally, the simulation results on benchmark functions show the efficiency of our algorithm.
引用
收藏
页码：4497 / +
页数：3
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