Please use this identifier to cite or link to this item:
Type: Artigo de periódico
Title: Hopfield neural networks in large-scale linear optimization problems
Author: Fontova, MIV
Oliveira, ARL
Lyra, C
Abstract: Hopfield neural networks and affine scaling interior point methods are combined in a hybrid approach for solving linear optimization problems. The Hopfield networks perform the early stages of the optimization procedures, providing enhanced feasible starting points for both primal and dual affine scaling interior point methods, thus facilitating the steps towards optimality. The hybrid approach is applied to a set of real world linear programming problems. The results show the potential of the integrated approach, indicating that the combination of neural networks and affine scaling interior point methods can be a good alternative to obtain solutions for large-scale optimization problems. (C) 2011 Elsevier Inc. All rights reserved.
Subject: Hopfield networks
Interior point methods
Affine scaling methods
Linear programming
Neural networks
Country: EUA
Editor: Elsevier Science Inc
Citation: Applied Mathematics And Computation. Elsevier Science Inc, v. 218, n. 12, n. 6851, n. 6859, 2012.
Rights: fechado
Identifier DOI: 10.1016/j.amc.2011.12.059
Date Issue: 2012
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
WOS000299847700025.pdf178.36 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.