%0 Journal Article
%A Nazemi, A.
%A Sukhtsaraee, S.
%A Mortezaee, M.
%T An efficient modified neural network for solving nonlinear programming problems with hybrid constraints
%J Journal of Operational Research and Its Applications
%V 16
%N 3
%U http://jamlu.liau.ac.ir/article-1-1632-en.html
%R
%D 2019
%K Convex programming, Lyapunov stability, Hybrid constraints, Neural network, Globally convergent,
%X This paper presents the optimization techniques for solving convex programming problems with hybrid constraints. According to the saddle point theorem, optimization theory, convex analysis theory, Lyapunov stability theory and LaSalleinvariance principle, a neural network model is constructed. The equilibrium point of the proposed model is proved to be equivalent to the optimal solution of the original problem. It is also shown that the proposed network model is stable in the Lyapunov sense and it is globally convergent to an exact optimal solution of the original problem. Several practical examples are provided to show the feasibility and the efficiency of the method.
%> http://jamlu.liau.ac.ir/article-1-1632-en.pdf
%P 1-20
%& 1
%!
%9 Research
%L A-11-1399-2
%+ Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
%G eng
%@ 2251-7286
%[ 2019