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

Ali Mehdi Nezhadroshan; Amir Mohammad Fathollahi-Fard; Mostafa Hajiaghaei-Keshteli

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

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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.

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《International journal of systems science. Operations & logistics》 |2021年第4期|321-347|共27页
作者
Ali Mehdi Nezhadroshan; Amir Mohammad Fathollahi-Fard; Mostafa Hajiaghaei-Keshteli;
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作者单位

Department of Management, Islamic Azad University, Tehran, Iran;

Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran, Department of Electrical Engineering, Ecole de Technologie Superieure, University of Quebec, Montreal, Canada;

Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran;

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正文语种英语
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Stochastic programming; supply chain; humanitarian logistics; relief chain; resiliency; multiple disasters;

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

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