Integrated and Coordinated Relief Logistics and Road Recovery Planning Problem

Akbari, Vahid; Sayarshad, Hamid R

Abstract

Sudden onset disasters can block roads and hinder relief logistics. With the objective of facilitating access to critical locations in the disaster-stricken area, we propose a new mathematical model that determines the schedule and routes of a relief distribution team and a road restoration team. The road restoration team restores some of the blocked roads to provide faster access to critical nodes for the relief distribution team. We study the case in which the restoration times are stochastic, and our goal is to minimize the time by which the last demand node is met by the relief distribution team. We provide a detailed case study of our model with real data from Harris County in Texas, which was impacted by Hurricane Harvey during 2017. The results obtained from testing our model show that the objective function is decreased by up to 15% using the proposed non-myopic policy.

Citation

Akbari, V., & Sayarshad, H. R. (2022). Integrated and Coordinated Relief Logistics and Road Recovery Planning Problem. Transportation Research Part D: Transport and Environment, 111, Article 103433. https://doi.org/10.1016/j.trd.2022.103433

• Journal Article Type: Article
• Acceptance Date: Sep 12, 2022
• Online Publication Date: Sep 12, 2022
• Publication Date: 2022-10
• Deposit Date: Sep 20, 2022
• Publicly Available Date: Sep 13, 2023
• Journal: Transportation Research Part D: Transport and Environment
• Print ISSN: 1361-9209
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 111
• Article Number: 103433
• DOI: https://doi.org/10.1016/j.trd.2022.103433
• Keywords: Markov decision process (MDP); humanitarian logistics; road restoration; relief distribution; disaster response; restoration equipment positioning
• Public URL: https://nottingham-repository.worktribe.com/output/11465171
• Publisher URL: https://www.sciencedirect.com/science/article/abs/pii/S1361920922002590