Journal
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
Volume 234, Issue 2, Pages 505-511Publisher
ELSEVIER
DOI: 10.1016/j.cam.2009.12.041
Keywords
Convex quadratic bilevel programming; Asymptotic stability; Neural network; Optimal solution
Categories
Funding
- National Natural Science Foundation of China [10926168, 70771080]
Ask authors/readers for more resources
A neural network is proposed for solving a convex quadratic bilevel programming problem. Based on Lyapunov and LaSalle theories, we prove strictly an important theoretical result that, for an arbitrary initial point, the trajectory of the proposed network does converge to the equilibrium, which corresponds to the optimal solution of a convex quadratic bilevel programming problem. Numerical simulation results show that the proposed neural network is feasible and efficient for a convex quadratic bilevel programming problem. (C) 2010 Elsevier By. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available