Bee Colony Optimization Approach to Solving the Anticovering Location Problem

Abstract

Bee colony optimization (BCO) is a relatively new metaheuristic designed to deal with hard combinatorial optimization problems. It belongs to the group of nature-inspired methods that explore collective intelligence applied by the honey bees during the nectar collecting process. In this paper, BCO is applied to the anticovering location problem (ACLP), one of the fundamental problems in the area of discrete location. Because a BCO algorithm has not been used in the literature related to the ACLP so far, it was a challenge to test its performances on this nondeterministic polynomial time (NP)-hard problem. The numerical experiments performed on the well known benchmark problems show that the proposed algorithm can generate high-quality solutions in reasonable CPU times.