Design and analysis of an efficient neural network model for solving nonlinear optimization problems

DOI10.1080/00207720500282359zbMath1126.90406OpenAlexW1963493259MaRDI QIDQ5426614

Lucia Valeria de Arruda, Wagner Caradori do Amaral, Ivan Nunes da Silva

Publication date: 13 November 2007

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207720500282359

zbMATH Keywords

nonlinear programmingrecurrent neural networksHopfield networksconstrained optimization problems

Mathematics Subject Classification ID

Nonlinear programming (90C30) Learning and adaptive systems in artificial intelligence (68T05) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (1)

A review of Hopfield neural networks for solving mathematical programming problems

Cites Work

• Multilayer perceptron for nonlinear programming
• Robust estimation of parametric membership regions
• A projection neural network and its application to constrained optimization problems
• Neurons with graded response have collective computational properties like those of two-state neurons.

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