Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/28963
Title: Allocation of temporary disaster response facilities under demand uncertainty: An earthquake case study
Authors: Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.
0000-0001-8054-5606
0000-0001-6877-2937
0000-0002-9445-6740
Çavdur, Fatih
Köse, Merve Küçük
Sebatlı, Aslı
AAE-4504-2019
AAC-2099-2020
AAG-9471-2021
8419687000
57191227592
57191223084
Keywords: Geology
Meteorology & atmospheric sciences
Water resources
Disaster operations management
Disaster relief operations
Facility allocation
Relief supplies distribution
Temporary disaster response facility
Stochastic programming
Emergency response
OR/MS research
Evacuation
Model
Optimization
Formulation
Location
Issue Date: 1-Oct-2016
Publisher: Elsevier
Citation: Çavdur, F. vd. (2016). "Allocation of temporary disaster response facilities under demand uncertainty: An earthquake case study". International Journal of Disaster Risk Reduction, 19, 159-166.
Abstract: In this paper, we consider the problem of temporary disaster response facility allocation for temporary or short-term disaster relief operations, propose a solution approach and illustrate it with an earthquake case study in Turkey. A two-stage stochastic program is developed for the solution of the problem to minimize the total distance traveled, the unmet demand and the total number of facilities (considering the potential difficulties to access the facilities), where facility allocation and service decisions are performed in the first and second stages, respectively. An earthquake case study developed by the Prime Ministry Disaster and Emergency Management Authority (mostly referred as AFAD in Turkey) is used to test our model. We use five different scenarios, each representing a different after-disaster situation (i.e., traffic conditions, time etc.), with its respective probability of occurrence, to model the demand uncertainty for relief supplies. We first solve the deterministic model for each scenario, and then, the corresponding stochastic program. In addition to the defined objectives of the model, quality of each solution is analyzed in terms of average walking distance, demand satisfaction rate and average facility utilization.
URI: https://doi.org/10.1016/j.ijdrr.2016.08.009
https://www.sciencedirect.com/science/article/pii/S2212420916301522
http://hdl.handle.net/11452/28963
ISSN: 2212-4209
Appears in Collections:Scopus
Web of Science

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