Solving a class of facility location problems using genetic algorithms

Abstract

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.