NDLI: The decision method of emergency supplies collection with fuzzy demand constraint under background of sudden disaster

Content Provider	Springer Nature Link
Author	Xing, Huang
Copyright Year	2016
Abstract	As the stages of emergency response shift, it is an important task in the early stage of emergency response to handle emergency supply (ES) collection with fuzzy demand and multi-hub ES collection network. Taking into consideration the constraints such as no limit to collection time, capacity constraint to single hubs and different demand levels to be met by collection, this paper aims at establishing a mathematic planning model with two objectives, namely the shortest collection time and the optimal collection cost. In terms of algorithm design, the sequential enumeration method (SEM) was employed to solve the model, for higher iteration efficiency and lower difficulty level of the algorithm. The first step was to find the optimal ES collection time, collection route and allocation program in the direct shipment mode, the hub-and-spoke mode and the mixed mode. Then, the three modes were compared in terms of the collection route planning, the shortest collection time, the shortest collection route and the optimal collection cost of the entire ES collection network. The numerical example showed that compared with the simulated annealing (SA) algorithm, the result of SEM is basically the same with that of SA algorithm; however, SEM is simpler, more practical and easier to operate, so that it is of better promotional value.
Starting Page	869
Ending Page	886
Page Count	18
File Format	PDF
ISSN	0921030X
Journal	Natural Hazards
Volume Number	85
Issue Number	2
e-ISSN	15730840
Language	English
Publisher	Springer Netherlands
Publisher Date	2016-10-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Emergency logistics Collection optimization Sequential enumeration method (SEM) Disaster Fuzzy demand Natural Hazards Hydrogeology Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Civil Engineering Environmental Management
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science Water Science and Technology

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