A neural network approach for solving nonlinear bilevel programming problem

被引：29
|
作者：
Lv, Yibing [1 ]
Hu, Tiesong [1 ]
Wang, Guangmin [1 ]
Wan, Zhongping [2 ]
机构：
[1] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
来源：
COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2008年 / 55卷 / 12期
基金：
中国国家自然科学基金;
关键词：
nonlinear bilevel programming; neural network; asymptotic stability; optimal solution;
D O I：
10.1016/j.camwa.2007.09.010
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A neural network model is presented for solving nonlinear bilevel programming problem, which is a NP-hard problem. The proposed neural network is proved to be Lyapunov stable and capable of generating approximal 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. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2823 / 2829
页数：7
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