Solving Euclidean multifacility location problems under circular area constraints using Rprop

The present work considers multifacility location problems with circular area constraints having interactions between sources and destinations. A detailed literature survey reveals that a little attention has been paid to problem involving area constraints. Mathematical formulation and the analytical solutions have been obtained by using Kuhn-Tucker theory. The mathematical solution procedure is very complex and time consuming. Hence, an attempt has been made to get the solution of a complex, constrained multifacility location problem using artificial neural networks ANN. With the help of numerical examples, it has been established that within the acceptable limits resilient back-propagation Rprop model compares well with those obtained through analytical method.