A novel neural network for solving convex quadratic programming problems subject to equality and inequality constraints

This paper proposes a neural network model for solving convex quadratic programming (CQP) problems, whose equilibrium points coincide with Karush–Kuhn–Tucker (KKT) points of the CQP problem. Using the equality transformation and Fischer–Burmeister (FB) function, we construct the neural network model...

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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 214; pp. 23 - 31
Main Authors:	Huang, Xinjian, Lou, Xuyang, Cui, Baotong
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 19.11.2016
Subjects:	Convex quadratic programming Fischer-Burmeister function Neural network Stability Convex quadratic programming Fischer-Burmeister function Stability Neural network
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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