A neural network approach for nonlinear bilevel programming problem

被引：7
|
作者：
Lv, Yibing [1 ]
Hu, Tiesong [1 ]
Wan, Zhongping
机构：
[1] Wuhan Univ, Inst Syst Engn, Wuhan 430072, Peoples R China
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007) | 2007年
关键词：
nonlinear bilevel programming; neural network; asymptotic stability; optimal solution;
D O I：
10.2991/iske.2007.39
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel neural network approach is presented for solving nonlinear bilevel programming problem. The proposed neural network is proved to be Lyapunov stable and capable of generating optimal solution to the nonlinear bilevel programming problem. The asymptotic properties of the neural network are analyzed and the condition for asymptotic stability, solution feasibility and solution optimality are derived. The transient behavior of the neural network is simulated and the validity of the network is verified with numerical examples.
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