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
volume 1 issue 1
pages 55- 67
publication date 2016-08-01
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