Neighborhood decomposition based variable neighborhood search for the capacitated p-median problem

Capacitated p-median problem (CPMP) is a combinatorial optimization problem with several applications. In this article, we propose an efficient heuristic approach called the neighborhood decomposition based variable neighborhood search (NDVNS) algorithm for the CPMP. The proposed algorithm combines an efficient variable neighborhood search method and an neighborhood decomposition strategy. Experimental results on 3 sets of benchmark instances show that the proposed NDVNS algorithm performs well on the small-scale instances compared to some existing algorithms in the literature. In particular, the proposed algorithm is able to obtain the best known solution for all the tested instances in a short computational time.