Numerical solution for linear and quadratic programming problems using a recurrent neural network

被引：21
|
作者：
Malek, A. [1 ]
Alipour, M. [1 ]
机构：
[1] Tarbait Modarres Univ, Dept Math, Tehran, Iran
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2007年 / 192卷 / 01期
关键词：
linear and quadratic programming; neural networks; dynamical systems;
D O I：
10.1016/j.amc.2007.02.149
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A recurrent neural network, is proposed in this paper for solving linear and quadratic programming problems. The main advantage of this network is that here we are not in need of parameters setting. Moreover, using this network we can solve primal programming problems and their duals simultaneously. We prove the global convergence of the neural network and demonstrate the advanced performance of the proposed network by means of simulation of several numerical examples. (c) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码：27 / 39
页数：13
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