A disaster relief commodity supply chain network considering emergency relief volunteers: a case study. Issue 3 (9th April 2021)

• Record Type: Journal Article
• Authors: Kebriyaii, Omid; Hamzehei, Marzieh; Khalilzadeh, Mohammad
• Is Part Of: Journal of humanitarian logistics and supply chain management. Volume 11:Issue 3(2021)
• Page Start: 493
• Page End: 521
• Publication Date: 2021-04-09
• Subjects: Disaster relief -- Commodity distribution -- Supply chain -- Emergency relief volunteers -- Robust fuzzy stochastic programming; Humanitarian assistance -- Management -- Periodicals; Emergency management -- Periodicals; Disaster relief -- Periodicals; Business logistics -- Periodicals; 361.26
• DOI: 10.1108/JHLSCM-08-2020-0073
• Languages: English
• ISSNs: 2042-6747

Abstract

Abstract : Purpose: The number of natural and man-made disasters is remarkable and threatened human lives at the time of occurrence and also after that. Therefore, an efficient response following a disaster can eliminate or mitigate the adverse effects. This paper aims to help address those challenges related to humanitarian logistics by considering disaster network design under uncertainty and the management of emergency relief volunteers simultaneously. Design/methodology/approach: In this paper, a robust fuzzy stochastic programming model is proposed for designing a relief commodity supply chain network in a disaster by considering emergency relief volunteers. To demonstrate the practicality of the proposed model, a case study is presented for the 22 districts of Tehran and solved by an exact method. Findings: The results indicate that there are many parameters affecting the design of a relief commodity supply chain network in a disaster, and also many parameters should be controlled so that, the catastrophe is largely prevented and the lives of many people can be saved by sending the relief commodity on time. Practical implications: This model helps decision-makers and authorities to explore optimal location and allocation decisions without using complex optimization algorithms. Originality/value: To the best of the authors' knowledge, employee workforce management models have not received adequate attention despite their role in relief and recovery efforts. Hence, the proposed model focuses on the problem of managing employees and designing a disaster logistics network simultaneously. The robust fuzzy stochastic programming method is applied for the first time for controlling the uncertainties in the design of humanitarian relief supply chains.