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Hopfield neural networks in large-scale linear optimization problems

By MIV Fontova, ARL Oliveira and C Lyra

Abstract

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)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.2181268516859Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Topics: Hopfield networks, Optimization, Interior point methods, Affine scaling methods, Linear programming, Neural networks, Interior-point Methods, Warm-start, Algorithm, Implementation, Programs
Publisher: EUA
Year: 2015
DOI identifier: 10.1016/j.amc.2011.12.059
OAI identifier: oai:repositorio.unicamp.br:REPOSIP/69634
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