Solving Location-allocation Problems with Rectilinear Distances by Simulated Annealing

Abstract

The objective of this study is to use the simulated annealing method to solve minisum location-allocation problems with rectilinear distances. The major advantage of the simulated annealing method is that it is a very general and efficient algorithm for solving combinatorial optimization problems with know objective functions. In this study, a simulated annealing algorithm was developed to solve the location-allocation problems, and its performance was compared with two other popular methods for solving location-allocation problems. The results show that simulated annealing is a good alternative to the two methods, as measured by both the solution quality and the computational time.