Name
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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.camwa.2007.09.010 | Computers & Mathematics with Applications |
Keywords | Field | DocType |
optimal solution,nonlinear bilevel programming problem,solution optimality,neural network,nonlinear bilevel programming,asymptotic property,asymptotic stability,neural network model,neural network approach,approximal optimal solution,np-hard problem,solution feasibility,proposed neural network,np hard problem,bilevel programming | Lyapunov function,Mathematical optimization,Nonlinear system,Bilevel optimization,Exponential stability,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
55 | 12 | Computers and Mathematics with Applications |
Citations | PageRank | References |
12 | 0.67 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yibing Lv | 1 | 90 | 6.44 |
| Tiesong Hu | 2 | 69 | 5.31 |
| Guangmin Wang | 3 | 180 | 14.73 |
| Zhongping Wan | 4 | 208 | 19.04 |