Facility location selection using community-based single swap: A case study

This paper focuses on the uncapacitated k-median facility location problem, which asks to locate k facilities in a network that minimize the total routing time, taking into account the constraints of nodes that are able to serve as servers and clients, as well as the level of demand in each client node. This problem is important in a wide range of applications from operation research to mobile ad-hoc networks. Existing algorithms for this problem often lead to high computational costs when the underlying network is very large, or when the number k of required facilities is very large. We aim to improve existing algorithms by taking into considerations of the community structures of the underlying network. More specifically, we extend the strategy of local search with single swap with a community detection algorithm. As a real-world case study, we analyze in detail Auckland North Shore spatial networks with varying distance threshold and compare the algorithms on these networks. The results show that our algorithm significantly reduces running time while producing equally optimal results.