A neural network approach for nonlinear bilevel programming problem
- 10.2991/iske.2007.39How to use a DOI?
- nonlinear bilevel programming; neural network; asymptotic stability; optimal solution
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.
- © 2007, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yibing Lv AU - Tiesong Hu AU - Zhongping Wan PY - 2007/10 DA - 2007/10 TI - A neural network approach for nonlinear bilevel programming problem BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 226 EP - 230 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.39 DO - 10.2991/iske.2007.39 ID - Lv2007/10 ER -