On solving nonlinear programming problems via Neural Networks

被引：0
|
作者：
Mladenov, V.M. [1 ]
Maratos, N.G. [1 ]
Tsakoumis, A.C. [1 ]
Tashev, T.A. [1 ]
Mastorakis, N.E. [1 ]
机构：
[1] Faculty of Automatics, Technical University of Sofia, 1756 Sofia, Bulgaria
来源：
Neural Network World | 2001年 / 11卷 / 03期
关键词：
Convex programming;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper we consider several Neural Network architectures for solving nonlinear programming problems with inequality constrains. This is an extension of previous authors' work and here we present a new architecture for convex programming problems. The architecture is based on alternative pseudo-cost function, which do not require large penalty parameter values. Simulation results based on SIMULINK&reg models are given and compared.
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页码：293 / 304
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