Routing multiple work teams to minimize latency in post-disaster road network restoration

Ajam, Meraj; Akbari, Vahid; Salman, F. Sibel

Abstract

After a disaster, often roads are damaged and blocked, hindering accessibility for relief efforts. It is essential to dispatch work teams to restore the blocked roads by clearance or repair operations. With the goal of enabling access between critical locations in the disaster area in shortest time, we propose algorithms that determine the schedule and routes of multiple work teams. We minimize the total latency of reaching the critical locations, where the latency of a location is defined as the time it takes from the start of the operation until its first visit by one of the work teams. Coordination among the teams is needed since some blocked edges might be opened by a certain team and utilized by other teams later on. First, we develop an exact mathematical model that handles the coordination requirement. After observing the intractability of this formulation, we introduce two heuristic methods and a lower bounding procedure. In the first method, we develop a mathematical model based on a novel multi-level network representation that yields solutions with disjoint paths. Given that it does not coordinate the teams, we present a matheuristic based on a cluster-first-route-second approach embedded into a local search algorithm together with an additional coordination step to obtain alternative solutions with higher quality and in a shorter time. We test our heuristics on data sets coming from a real network from the literature (180 instances) and randomly generated ones (640 instances) and observe the superiority of the solutions obtained by incorporation of coordination.

Citation

Ajam, M., Akbari, V., & Salman, F. S. (2022). Routing multiple work teams to minimize latency in post-disaster road network restoration. European Journal of Operational Research, 300(1), 237-254. https://doi.org/10.1016/j.ejor.2021.07.048

• Journal Article Type: Article
• Acceptance Date: Jul 28, 2021
• Online Publication Date: Aug 4, 2021
• Publication Date: Jul 1, 2022
• Deposit Date: Aug 24, 2021
• Publicly Available Date: Aug 5, 2023
• Journal: European Journal of Operational Research
• Print ISSN: 0377-2217
• Electronic ISSN: 1872-6860
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 300
• Issue: 1
• Pages: 237-254
• DOI: https://doi.org/10.1016/j.ejor.2021.07.048
• Keywords: Information Systems and Management; Management Science and Operations Research; Modelling and Simulation; General Computer Science; Industrial and Manufacturing Engineering
• Public URL: https://nottingham-repository.worktribe.com/output/6089584
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0377221721006585