solving linear semi-infinite programming problems using recurrent neural networks
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abstract
linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints. in this paper, to solve this problem, we combine a discretization method and a neural network method. by a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem. then, we use a recurrent neural network model, with a simple structure based on a dynamical system to solve this problem. the portfolio selection problem and some other numerical examples are solved to evaluate the effectiveness of the presented model.
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Journal title:
biquarterly journal of control and optimization in applied mathematicsPublisher: payame noor university
ISSN
volume 1
issue 1 2015
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