Computers and Industrial Engineering, ( ISI ), Volume (66), No (1), Year (2013-12) , Pages (212-221)

Title : ( An application of a merit function for solving convex programming problems )

Authors: Alireza Nazemi , Sohrab Effati ,

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This paper presents a gradient neural network model for solving convex nonlinear programming (CNP) problems. The main idea is to convert the CNP problem into an equivalent unconstrained minimization problem with objective energy function. A gradient model is then de- ¯ned directly using the derivatives of the energy function. It is also 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. It is also found that a larger scaling factor leads to a better convergence rate of the trajectory. The validity and transient behavior of the neural network are demonstrated by using various examples.

Keywords

, Neural network, convex programming, NCP-function, merit function, convergent,
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@article{paperid:1035645,
author = {Alireza Nazemi and Effati, Sohrab},
title = {An application of a merit function for solving convex programming problems},
journal = {Computers and Industrial Engineering},
year = {2013},
volume = {66},
number = {1},
month = {December},
issn = {0360-8352},
pages = {212--221},
numpages = {9},
keywords = {Neural network; convex programming; NCP-function; merit function; convergent; sta- bility.},
}

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%0 Journal Article
%T An application of a merit function for solving convex programming problems
%A Alireza Nazemi
%A Effati, Sohrab
%J Computers and Industrial Engineering
%@ 0360-8352
%D 2013

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