A Hybrid Swarm Intelligence Approach for Anti-Covering Location Problem

Given a set of potential facility location sites, the anti-covering location problem (ACLP) seeks a maximum weighted set of facilities located in such a way that no two placed facilities are inside a pre-specified distance of one another. The total number of facilities to be sited is not known in advance in ACLP. It is an NP-hard problem. It finds application in locating undesirable facilities, telecommunications equipment siting, locating military defence units and locating franchise outlets. This paper focuses on presenting an Ant Colony Optimization (ACO) algorithm tailored for the un-weighted ACLP. The ACO is a swarm intelligence technique motivated by the foraging behavior of real ants. Our proposed approach uses ACO algorithm in combination with local search heuristics to solve ACLP. Based on the computational experiments performed by us, it can be concluded that the proposed approach performs as good as or better than the available state-of-the-art approaches.