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Mathematical Models in Humanitarian Supply Chain Management: A Systematic Literature Review

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  • Muhammad Salman Habib
  • Young Hae Lee
  • Muhammad Saad Memon

Abstract

In the past decade the humanitarian supply chain (HSC) has attracted the attention of researchers due to the increasing frequency of disasters. The uncertainty in time, location, and severity of disaster during predisaster phase and poor conditions of available infrastructure during postdisaster phase make HSC operations difficult to handle. In order to overcome the difficulties during these phases, we need to assure that HSC operations are designed in an efficient manner to minimize human and economic losses. In the recent times, several mathematical optimization techniques and algorithms have been developed to increase the efficiency of HSC operations. These techniques and algorithms developed for the field of HSC motivate the need of a systematic literature review. Owing to the importance of mathematical modelling techniques, this paper presents the review of the mathematical contributions made in the last decade in the field of HSC. A systematic literature review methodology is used for this paper due to its transparent procedure. There are two objectives of this study: the first one is to conduct an up-to-date survey of mathematical models developed in HSC area and the second one is to highlight the potential research areas which require attention of the researchers.

Suggested Citation

  • Muhammad Salman Habib & Young Hae Lee & Muhammad Saad Memon, 2016. "Mathematical Models in Humanitarian Supply Chain Management: A Systematic Literature Review," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-20, February.
    • Handle: RePEc:hin:jnlmpe:3212095
    DOI: 10.1155/2016/3212095
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    Cited by:

    1. Elfe Buluc & Meltem Peker & Bahar Y. Kara & Manoj Dora, 2022. "Covering vehicle routing problem: application for mobile child friendly spaces for refugees," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 461-484, June.
    2. Francisca Santana-Robles & Eva Selene Hernández-Gress & Ricardo Martínez-López & Isidro Jesús González-Hernández, 2024. "Quick-Response Model for Pre- and Post-Disaster Evacuation and Aid Distribution: The Case of the Tula River Flood Event," Logistics, MDPI, vol. 8(1), pages 1-21, January.
    3. Shaw, Lipika & Das, Soumen Kumar & Roy, Sankar Kumar, 2022. "Location-allocation problem for resource distribution under uncertainty in disaster relief operations," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    4. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    5. Maria Rossana D. de Veluz & Anak Agung Ngurah Perwira Redi & Renato R. Maaliw & Satria Fadil Persada & Yogi Tri Prasetyo & Michael Nayat Young, 2023. "Scenario-Based Multi-Objective Location-Routing Model for Pre-Disaster Planning: A Philippine Case Study," Sustainability, MDPI, vol. 15(6), pages 1-33, March.
    6. Gabriel Zayas‐Cabán & Emmett J. Lodree & David L. Kaufman, 2020. "Optimal Control of Parallel Queues for Managing Volunteer Convergence," Production and Operations Management, Production and Operations Management Society, vol. 29(10), pages 2268-2288, October.
    7. Vosooghi, Zeinab & Mirzapour Al-e-hashem, S.M.J. & Lahijanian, Behshad, 2022. "Scenario-based redesigning of a relief supply-chain network by considering humanitarian constraints, triage, and volunteers’ help," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    8. Dayanna Rodrigues da Cunha Nunes & Orivalde Soares da Silva Júnior & Renata Albergaria de Mello Bandeira & Yesus Emmanuel Medeiros Vieira, 2023. "A Robust Stochastic Programming Model for the Well Location Problem: The Case of The Brazilian Northeast Region," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    9. Hossein Baharmand & Diego Vega & Matthieu Lauras & Tina Comes, 2022. "A methodology for developing evidence-based optimization models in humanitarian logistics," Annals of Operations Research, Springer, vol. 319(1), pages 1197-1229, December.
    10. Cao, Cejun & Liu, Yang & Tang, Ou & Gao, Xuehong, 2021. "A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains," International Journal of Production Economics, Elsevier, vol. 235(C).
    11. Paret, Kyle E. & Mayorga, Maria E. & Lodree, Emmett J., 2021. "Assigning spontaneous volunteers to relief efforts under uncertainty in task demand and volunteer availability," Omega, Elsevier, vol. 99(C).

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