Multi-period hub location problem with serial demands: A case study of humanitarian aids distribution in Lebanon. (May 2021)

• Record Type: Journal Article
• Authors: Neamatian Monemi, Rahimeh; Gelareh, Shahin; Nagih, Anass; Maculan, Nelson; Danach, Kassem
• Is Part Of: Transportation research. Volume 149(2021)
• Publication Date: 2021-05
• Subjects: Hub-and-spoke network design -- Distribution -- Humanitarian aids -- Refugees -- Mateheuristics; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2020.102201
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: Multi-period hub location problem with a particular demand pattern resulted by the user's behaviour. A case study of Lebanese experience in Syrian war refugee accommodation is studiedseveral classes of valid inequalities together with separation procedures leading to a cut-and-Benders approach computational experiments on the case study with real data as well as randomly generated instances. Abstract: In this paper, we address the problem of humanitarian aids distribution across refugee camps in war-ridden areas from a network design perspective. We show that the problem can be modeled as a variant of multi-period hub location problem with a particular demand pattern resulted by the user's behavior. The problem has been motivated by a case study of Lebanese experience in Syrian war refugee accommodation. We elaborate on the complexity and real-life constraints and, propose a compact formulation of a mathematical model of the problem. We then show that modeling the problem using a Benders paradigm drives O ( n 3 ) variables of the original compact model unnecessary in addition to the constraints that are being projected out in a typical Benders decomposition. Additionally, we identify several classes of valid inequalities together with efficient separation procedures leading to a cut-and-Benders approach. Our extensive computational experiments on the case study with real data as well as randomly generated instances proves the performance of proposed solution methods.