Solving a System of Singular Perturbation Problems via Neural Networks

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 rational spectral collocation method for solving a class of parameterized singular perturbation problems

A new kind of numerical method based on rational spectral collocation with the sinh transformation is presented for solving parameterized singularly perturbed two-point boundary value problems with one boundary layer. By means of the sinh transformation, the original Chebyshev points are mapped onto the transformed ones clustered near the singular points of the problem. The results from asympto...

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...

Neural Networks for Solving Quadratic Assignment Problems

Abstract— In this paper the Hopfield neural networks are adopted to solve the quadratic assignment problem, which is a generalization of the traveling salesman’s problem (TSP), the graph-partitioning problem (GPP), and the matching problem. When the Hopfield neural network was applied alone, a sub-optimal solution was obtained. By adding the 2exchange we obtained a solution very close to the op...

Solving Constraint Satisfaction Problems Using Neural Networks