Neural approach for solving several types of optimization problems

DOI10.1007/S10957-006-9032-9zbMath1112.90106OpenAlexW2091375303MaRDI QIDQ857585

Ivan Nunes da Silva, Lúcia V. R. Arruda, Wagner C. Amaral

Publication date: 19 December 2006

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-006-9032-9

zbMATH Keywords

dynamic programmingcombinatorial optimizationnonlinear optimizationrecurrent neural networksHopfield network.

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59) Combinatorial optimization (90C27) Dynamic programming (90C39)

Related Items (1)

A review of Hopfield neural networks for solving mathematical programming problems

Cites Work

• Robust estimation of parametric membership regions
• Neurons with graded response have collective computational properties like those of two-state neurons.
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