A scenario-based possibilistic-stochastic programming approach to address resilient humanitarian logistics considering travel time and resilience levels of facilities

There is a great deal of interest in addressing humanitarian logistics due to the need for emergency services in the case of disaster. Controlling both operational and disruption uncertainties in the emergency management is one of challenging topics lately to propose a robust plan for humanitarian l...

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Veröffentlicht in:International journal of systems science. Operations & logistics Jg. ahead-of-print; H. ahead-of-print; S. 1 - 27
Hauptverfasser: Nezhadroshan, Ali Mehdi, Fathollahi-Fard, Amir Mohammad, Hajiaghaei-Keshteli, Mostafa
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Taylor & Francis 02.10.2021
Schlagworte:
humanitarian logistics
multiple disasters
relief chain
resiliency
Stochastic programming
supply chain
ISSN:2330-2674, 2330-2682
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Zusammenfassung:There is a great deal of interest in addressing humanitarian logistics due to the need for emergency services in the case of disaster. Controlling both operational and disruption uncertainties in the emergency management is one of challenging topics lately to propose a robust plan for humanitarian logistics. Designing a robust and resilient humanitarian relief chain networks under both operational and disruptive risks can ensure the delivery of the essential supplies to beneficiaries. In this paper, a humanitarian logistic network design with multiple central warehouses and local distribution centres in an integrated manner is addressed by a novel scenario-based possibilistic-stochastic programming approach. The main real-life application of the proposed methodology is to consider the transportation network's routes after an earthquake to provide a plan against uncertainty in whole levels of supply chain along with its availability. To this end, a real case study of Mazandaran province in the north of Iran is provided to validate our methodology as well as a comprehensive discussion and managerial insights are concluded from the results.
ISSN:2330-2674
2330-2682
DOI:10.1080/23302674.2020.1769766