期刊
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
卷 234, 期 2, 页码 505-511出版社
ELSEVIER
DOI: 10.1016/j.cam.2009.12.041
关键词
Convex quadratic bilevel programming; Asymptotic stability; Neural network; Optimal solution
资金
- National Natural Science Foundation of China [10926168, 70771080]
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.
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