A dynamic genetic algorithm based on continuous neural networks for a kind of non-convex optimization problems.

DOI10.1016/S0096-3003(03)00309-6zbMath1161.65333OpenAlexW2140851689MaRDI QIDQ1428599

Meisheng Xue, Qing Tao, Xin Liu

Publication date: 29 March 2004

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0096-3003(03)00309-6

zbMATH Keywords

neural networksGenetic algorithmquadratic programming problemssteepest decent method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Quadratic programming (90C20)

Related Items (2)

Solving a class of non-convex quadratic problems based on generalized KKT conditions and neurodynamic optimization technique ⋮ A neurodynamic optimization technique based on overestimator and underestimator functions for solving a class of non-convex optimization problems

Cites Work

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• A simple and high performance neural network for quadratic programming problems.
• Analysis and synthesis of a class of neural networks: linear systems operating on a closed hypercube
• A high performance neural network for solving nonlinear programming problems with hybrid constraints

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