QA296 : An application of a projection operator and dynamic systems for solving a class of nonlinear programming problems
Thesis > Central Library of Shahrood University > Mathematical Sciences > MSc > 2015
Authors:
Abstarct: A wide variety of scientific and engineering problems can be formulated as nonlinear
optimization problems (NOPs). One promising approach to solve the NOPs with high
dimension is to employ artificial neural networks. In this thesis we present two neural network
models for solving NOPs. The first model can solve convex nonlinear programming
problems (CNPPs) with the constraints of equality and inequality. The second model is
derived baxsed on projection function for solving nonconvex nonlinear programming problems
(NCNPPs). In addition, we also analyze the existence and the convergence of the
trajectory, and the stability properties of the neural networks models. The validity and
efficiency of the proposed neural networks are demonstrated by using numerical examples.
Keywords:
#Convex optimization #Neural network #KKT conditions #Stability Link
Keeping place: Central Library of Shahrood University
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Keeping place: Central Library of Shahrood University
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