Artículos de revistas
Hopfield neural networks in large-scale linear optimization problems
Registro en:
Applied Mathematics And Computation. Elsevier Science Inc, v. 218, n. 12, n. 6851, n. 6859, 2012.
0096-3003
WOS:000299847700025
10.1016/j.amc.2011.12.059
Autor
Fontova, MIV
Oliveira, ARL
Lyra, C
Institución
Resumen
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. 218 12 6851 6859 Fundação 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)