RT - Journal Article
T1 - An efficient modified neural network for solving nonlinear programming problems with hybrid constraints
JF - JAMLU
YR - 2019
JO - JAMLU
VO - 16
IS - 3
UR - http://jamlu.liau.ac.ir/article-1-1632-en.html
SP - 1
EP - 20
K1 - Convex programming
K1 - Lyapunov stability
K1 - Hybrid constraints
K1 - Neural network
K1 - Globally convergent
AB - 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.
LA eng
UL http://jamlu.liau.ac.ir/article-1-1632-en.html
M3
ER -