Solving a class of facility location problems using genetic algorithms

Locating p facilities to serve a number of customers is a problem in many areas of business. The problem is to determine p facility locations such that the weighted average distance traveled from all the demand points to their nearest facility sites is minimized. A variant of the p-median problem is one in which a maximum distance constraint is imposed between the demand point and its nearest facility location, also known as the p-median problem with maximum distance constraint. In this paper, we apply a fairly new methodology known as genetic algorithms to solve a relatively large sized constrained version of the p-median problem. We present our computational experience on the use of genetic algorithms for solving the constrained version of the p-median problem using two different data sets. Our comparative experimental experience shows that this solution procedure performs quite well compared with the results obtained from existing techniques.