Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is approximated. ANNs can be viewed as models of real systems, built by tuning parameters known as weights. In training the net, the problem is to find the weights that optimize its performance (i.e. to minimize the error ove...

A wide spectrum of “real world” problems, such as vehicle routing, machine and crew scheduling, facility location, portfolio analysis, electricity generation planning, and communication and transportation network design, demands the use of combinatorial optimization methods. By a combinatorial optimization problem, we mean a program where a linear or nonlinear objective function must be optimiz...