Title: Dynamic relief-demand management for emergency logistics operations under large-scale disasters
Authors: Sheu, Jiuh-Biing
運輸與物流管理系 註:原交通所+運管所
Department of Transportation and Logistics Management
Keywords: Emergency logistics operations;Relief-demand management;Multi-source data fusion;Fuzzy clustering;Entropy;TOPSIS
Issue Date: 1-Jan-2010
Abstract: 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) multicriteria 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. (C) 2009 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.tre.2009.07.005
http://hdl.handle.net/11536/6074
ISSN: 1366-5545
DOI: 10.1016/j.tre.2009.07.005
Journal: TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Volume: 46
Issue: 1
Begin Page: 1
End Page: 17
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