A neural network approach for nonlinear bilevel programming problem

DOI

10.2991/iske.2007.39How to use a DOI?

Keywords

nonlinear bilevel programming; neural network; asymptotic stability; optimal solution

Abstract

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.

Copyright

© 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/).

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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  -