Solving Linear Semi-Infinite Programming Problems Using Recurrent Neural Networks

‎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.