| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4943257 | Expert Systems with Applications | 2017 | 10 Pages |
Abstract
In this paper, a feedback neural network model is proposed to compute the solution of the mathematical programs with equilibrium constraints (MPEC). The MPEC problem is altered into an identical one-level non-smooth optimization problem, then a sequential dynamic scheme that progressively approximates the non-smooth problem is presented. Besides asymptotic stability, it is proven that the limit equilibrium point of the suggested dynamic model is a solution for the original MPEC problem. Numerical simulation of various types of MPEC problems shows the significance of the results. Moreover, the scheme is applied to compute the Stackelberg-Cournot-Nash equilibria.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Ahmad Golbabai, Soraya Ezazipour,