Warm start by Hopfield neural networks for interior point methods

Hopfield neural networks and interior point methods are used in an integrated way to solve linear optimization problems. The Hopfield network gives warm start for the primal–dual interior point methods, which can be way ahead in the path to optimality. The approaches were applied to a set of real wo...

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Bibliographic Details
Published in:Computers & operations research 2007-09, Vol.34 (9), p.2553-2561
Main Authors: Fontova, Marta I. Velazco, Oliveira, Aurelio R.L., Lyra, Christiano
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Connectionism. Neural networks
Exact sciences and technology
Hopfield networks
Linear programming
Neural networks
Operational research. Management science
Optimization techniques
Primal–dual interior point methods
Problem solving
Studies
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Summary:Hopfield neural networks and interior point methods are used in an integrated way to solve linear optimization problems. The Hopfield network gives warm start for the primal–dual interior point methods, which can be way ahead in the path to optimality. The approaches were applied to a set of real world linear programming problems. The integrated approaches provide promising results, indicating that there may be a place for neural networks in the “real game” of optimization.
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2005.09.019