Modeling and analysis of artificial neural networks applied in operations research

被引：0
|
作者：
da Silva, IN [1 ]
de Souza, AN [1 ]
Bordon, ME [1 ]
机构：
[1] UNESP, FE, DEE, Sch Engn,Dept Elect Engn, BR-17033360 Bauru, SP, Brazil
来源：
MANUFACTURING, MODELING, MANAGEMENT AND CONTROL, PROCEEDINGS | 2001年
关键词：
operations research; neural networks; linear programming; artificial intelligence; parameter optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a massive number of these computational elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving problems related to operations research. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.
引用
收藏
页码：315 / 320
页数：6
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