The maximum covering location problem (MCLP) is a key problem in facility location, with many applications and variants. One such variant is the dynamic (or multi-period) MCLP, which considers the installation of facilities across multiple time periods. To the best of our knowledge, no exact solution method has been proposed to tackle large-scale instances of this problem. To that end, in this work, we expand upon the current state-of-the-art branch-and-Benders-cut solution method in the static case, by exploring several acceleration techniques. Additionally, we propose a specialised local branching scheme, that uses a novel distance metric in its definition of subproblems and features a new method for efficient and exact solving of the subproblems. These methods are then compared through extensive computational experiments, highlighting the strengths of the proposed methodologies.
@article{arxiv.2309.00702,
title = {Accelerated Benders Decomposition and Local Branching for Dynamic Maximum Covering Location Problems},
author = {Steven Lamontagne and Margarida Carvalho and Ribal Atallah},
journal= {arXiv preprint arXiv:2309.00702},
year = {2023}
}
Comments
V2: Minor corrections for references and invalid URL