Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
469996 | Computers & Mathematics with Applications | 2008 | 7 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Yibing Lv, Tiesong Hu, Guangmin Wang, Zhongping Wan,