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Dynamic relief-demand management for emergency logistics operations under large-scale disasters


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  • Sheu, Jiuh-Biing
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    This paper presents a dynamic relief-demand management model for emergency logistics operations under imperfect information conditions in large-scale natural disasters. The proposed methodology consists of three steps: (1) data fusion to forecast relief demand in multiple areas, (2) fuzzy clustering to classify affected area into groups, and (3) multi-criteria decision making to rank the order of priority of groups. The results of tests accounting for different experimental scenarios indicate that the overall forecast errors are lower than 10% inferring the proposed method's capability of dynamic relief-demand forecasting and allocation with imperfect information to facilitate emergency logistics operations.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.

    Volume (Year): 46 (2010)
    Issue (Month): 1 (January)
    Pages: 1-17

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    Handle: RePEc:eee:transe:v:46:y:2010:i:1:p:1-17

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    Keywords: Emergency logistics operations Relief-demand management Multi-source data fusion Fuzzy clustering Entropy TOPSIS;


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    Cited by:
    1. Lin, Yen-Hung & Batta, Rajan & Rogerson, Peter A. & Blatt, Alan & Flanigan, Marie, 2012. "Location of temporary depots to facilitate relief operations after an earthquake," Socio-Economic Planning Sciences, Elsevier, vol. 46(2), pages 112-123.
    2. Najafi, Mehdi & Eshghi, Kourosh & Dullaert, Wout, 2013. "A multi-objective robust optimization model for logistics planning in the earthquake response phase," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 217-249.
    3. Allahviranloo, Mahdieh & Chow, Joseph Y.J. & Recker, Will W., 2014. "Selective vehicle routing problems under uncertainty without recourse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 68-88.
    4. Falasca, Mauro & Zobel, Christopher, 2012. "An optimization model for volunteer assignments in humanitarian organizations," Socio-Economic Planning Sciences, Elsevier, vol. 46(4), pages 250-260.
    5. Chen, Lichun & Miller-Hooks, Elise, 2012. "Optimal team deployment in urban search and rescue," Transportation Research Part B: Methodological, Elsevier, vol. 46(8), pages 984-999.
    6. Lu, Chung-Cheng, 2013. "Robust weighted vertex p-center model considering uncertain data: An application to emergency management," European Journal of Operational Research, Elsevier, vol. 230(1), pages 113-121.
    7. Berkoune, Djamel & Renaud, Jacques & Rekik, Monia & Ruiz, Angel, 2012. "Transportation in disaster response operations," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 23-32.


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