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Research Journal of Pharmacy and Technology
Year : 2016, Volume : 9, Issue : 10
First page : ( 1727) Last page : ( 1731)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2016.00347.4

Augmented lagrange multiplier method to solve quadratic programming problems in standard form: A neural network approach

Dr. Hameed W. Abdul, Dr. Rajendran P.*

School of Advanced Sciences, VIT University, Vellore-632 014, Tamil Nadu, India

*Corresponding authors Email: hameedvellore@yahoo.co.in, prajendran@vit.ac.in

Online published on 2 March, 2017.

Abstract

In this Paper, we present a neural network for solving the quadratic programming problems in real time by means of augmented Lagrange multiplier method for problems in standard form. It is shown that the proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem. Validity and transient behavior of the proposed neural network are demonstrated by some simulation results using MATLAB software.

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Keywords

Quadratic Programming Problems, augmented Lagrange multiplier method, Neural Network, MATLAB.

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