Solving Linear Semi-Innite Programming Problems Using Recurrent Neural Networks

ýLinear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraintsý. ýIn this paperý, ýto solve this problemý, ýwe combine a discretization method and a neural network methodý. ýBy a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problemý. ýThený, ýwe use a recurrent neural network modelý, ýwith a simple structure based on a dynamical system to solve this problemý. ýThe portfolio selection problem and some other numerical examples are solved to evaluate the effectiveness of the presented model.