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A Stock Pre-positioning Model to Maximize the Total Expected Relief Demand of Disaster Areas
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 Title & Authors
A Stock Pre-positioning Model to Maximize the Total Expected Relief Demand of Disaster Areas
Lee, Woon-Seek; Kim, Byung Soo; Opit, Prudensy Febreine;
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 Abstract
Stock pre-positioning is one of the most important decisions for preparing the stage of emergency logistics planning. In this paper, a mixed integer model for stock pre-positioning is derived to support an emergency disaster relief response against the event of earthquake. A maximum response time limit, budget availability, multiple item types, and capacity restrictions are considered. In the model, the decision of the distribution centers to cover a disaster area and the amount of supplies to be stocked in each distribution center are simultaneously determined to maximize the total expected relief demand of the disaster areas covered by the existing distribution centers. The proposed model is applied to a real case with 33 disaster areas and 16 distribution centers in Indonesia. Several sensitivity analyses are conducted to estimate the fluctuation on the emergency stock pre-positioning planning by changing the maximum response time and budgets.
 Keywords
Disaster Relief;Stock Pre-positioning;Emergency Logistics Response;
 Language
English
 Cited by
1.
Preservation of deteriorating seasonal products with stock-dependent consumption rate and shortages, Journal of Industrial and Management Optimization, 2016, 12, 4, 11  crossref(new windwow)
 References
1.
Balcik, B. and Beamon, B. M. (2008), Facility location in humanitarian relief, International Journal of Logistics: Research and Applications, 11(2), 101-121. crossref(new window)

2.
Beamon, B. M. (2004), Humanitarian relief chains: issues and challenges. in Proceedings of the 34th international Conference on Computers and Industrial Engineering, San Francisco, CA, 77-82.

3.
Beamon, B. M. and Kotleba, S. A. (2006), Inventory modelling for complex emergencies in humanitarian relief operations, International Journal of Logistics: Research and Applications, 9(1), 1-18. crossref(new window)

4.
Chang, M. S., Tseng, Y. L., and Chen, J. W. (2007), A scenario planning approach for the flood emergency logistics preparation problem under uncertainty, Transportation Research Part E: Logistics and Transportation Review, 43(6), 737-754. crossref(new window)

5.
Gatignon, A., Van Wassenhove, L. N., and Charles, A. (2010), The Yogyakarta earthquake: Humanitarian relief through IFRC's decentralized supply chain, International Journal of Production Economics, 126(1), 102-110. crossref(new window)

6.
National Agency for Disaster Management of Indonesia (2009), National Disaster Management Plan 2010-2014.

7.
Ortuno, M. T., Tirado, G., and Vitoriano, B. (2011), A lexicographical goal programming based decision support system for logistics of Humanitarian Aid, Top, 19(2), 464-479. crossref(new window)

8.
Ozbay, K. and Ozguven, E. E. (2007), Stochastic humanitarian inventory control model for disaster planning, Transportation Research Record: Journal of the Transportation Research Board, 2022(1), 63-75. crossref(new window)

9.
Ratick, S., Meacham, B., and Aoyama, Y. (2008), Locating backup facilities to enhance supply chain disaster resilience, Growth and Change, 39(4), 642-666. crossref(new window)

10.
Tovia, F. (2007), An emergency logistics response system for natural disasters, International Journal of Logistics: Research and Applications, 10(3), 173-186. crossref(new window)

11.
Yi, W. and Ozdamar, L. (2007), A dynamic logistics coordination model for evacuation and support in disaster response activities, European Journal of Operational Research, 179(3), 1177-1193. crossref(new window)