A note on the maximal covering location problem with customer preference ordering

Abstract

Recently a series of papers introduced and investigated the maximal covering location problem with customer preference ordering, a variant of the classical maximal covering location problem (MCLP). In these papers, mixed-integer bilevel optimization models and single-level reformulations were presented for this problem, as well as various heuristics such as a GRASP, a Tabu search and a variable neighborhood search. In this short note we show that instances of this new problem can actually be easily transformed into instances of the classical MCLP and this transformation even reduces the size of the instance. Thus, existing algorithms for the classical MCLP can be used to solve it. We provide a short computational study to show that this transformation leads to speed-ups of at least a magnitude when considering exact algorithms.