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http://dx.doi.org/10.7232/iems.2014.13.4.398

Humanitarian Relief Logistics with Time Restriction: Thai Flooding Case Study  

Manopiniwes, Wapee (Faculty of Science and Technology, Sophia University)
Nagasawa, Keisuke (Faculty of Science and Technology, Sophia University)
Irohara, Takashi (Faculty of Science and Technology, Sophia University)
Publication Information
Industrial Engineering and Management Systems / v.13, no.4, 2014 , pp. 398-407 More about this Journal
Abstract
Shortages and delays in a humanitarian logistics system can contribute to the pain and suffering of survivors or other affected people. Humanitarian logistics budgets should be sufficient to prevent such shortages or delays. Unlike commercial supply chain systems, the budgets for relief supply chain systems should be able to satisfy demand. This study describes a comprehensive model in an effort to satisfy the total relief demand by minimizing logistics operations costs. We herein propose a strategic model which determines the locations of distribution centers and the total inventory to be stocked for each distribution center where a flood or other catastrophe may occur. The proposed model is formulated and solved as a mixed-integer programming problem that integrates facility location and inventory decisions by considering capacity constraints and time restrictions in order to minimize the total cost of relief operations. The proposed model is then applied to a real flood case involving 47 disaster areas and 13 distribution centers in Thailand. Finally, we discuss the sensitivity analysis of the model and the managerial implications of this research.
Keywords
Humanitarian Logistics; Relief Supply Chain; Disaster Management; Optimization;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Afshar, A. and Haghani, A. (2012), Modeling integrated supply chain logistics in real-time large-scale disaster relief operations, Socio-Economic Planning Sciences, 46(4), 327-338.   DOI   ScienceOn
2 Balcik, B. and Beamon, B. M. (2008), Facility location in humanitarian relief, International Journal of Logistics, 11(2), 101-121.   DOI   ScienceOn
3 Department of Disaster Prevention and Mitigation, Ministry of Interior of the Royal Thai Government (2012), Statistics of floods in Thailand from 1989-2011.
4 Dilley, M., Chen, R. S., Deichmann, U., Lerner-Lam, A. L., and Arnold, M. (2005), Natural Disaster Hotspots: A Global Risk Analysis, World Bank, Washington, DC.
5 Ganeshan, S. and Diamond, W. (2009), Forecasting the numbers of people affected annually by natural disasters up to 2015, Research Report, Oxfam, Oxford, UK.
6 Irohara, T., Kuo, Y. H., and Leung, J. M. (2013), From preparedness to recovery: a tri-level programming model for disaster relief planning, Proceedings of the 4th International Conference on Computational Logistics (ICCL2013), Copenhagen, Denmark, 213-228.
7 Ji, G. and Zhu, C. (2012), A study on emergency supply chain and risk based on urgent relief service in disasters, Systems Engineering Procedia, 5, 313-325.   DOI   ScienceOn
8 Kongsomsaksakul, S., Yang, C., and Chen, A. (2005), Shelter location-allocation model for flood evacuation planning, Journal of the Eastern Asia Society for Transportation Studies, 6(1), 4237-4252.
9 Kovacs, G. and Spens, K. M. (2012), Relief Supply Chain Management for Disasters: Humanitarian Aid and Emergency Logistics, Information Science Reference, Hershey, PA.
10 Manopiniwes, W. and Irohara, T. (2014), A review of relief supply chain optimization, Industrial Engineering and Management Systems, 13(1), 1-14.   DOI   ScienceOn
11 McCall, V. M. (2006), Designing and pre-positioning humanitarian assistance pack-up kits (HA PUKs) to support pacific fleet emergency relief operations, Master's thesis, Naval Postgraduate School, Monterey, CA.
12 Nikbakhsh, E. and Zanjirani Farahani, R. (2011), Humanitarian logistics planning in disaster relief operations. In: Farahani, R. Z. et al. (eds.), Logistics Operations and Management: Concepts and Models, Elsevier, Waltham, MA, 291-332.
13 Rawls, C. G. and Turnquist, M. A. (2010), Pre-positioning of emergency supplies for disaster response, Transportation Research Part B: Methodological, 44(4), 521-534.   DOI   ScienceOn
14 Sheu, J. B. (2007), An emergency logistics distribution approach for quick response to urgent relief demand in disasters, Transportation Research Part E: Logistics and Transportation Review, 43(6), 687-709.   DOI   ScienceOn
15 The World Bank (2012), Thai Flood 2011: Rapid Assessment for Resilient Recovery and Reconstruction Planning, World Bank, Washington, DC.
16 Van Westen, C. J. (2013), Remote sensing and GIS for natural hazards assessment and disaster risk management. In: Shroder, J. F. (ed.), Treatise on Geomorphology, Academic Press, Waltham, MA, 259-298.
17 Tzeng, G. H., Cheng, H. J., and Huang, T. D. (2007), Multi-objective optimal planning for designing relief delivery systems, Transportation Research Part E: Logistics and Transportation Review, 43(6), 673-686.   DOI   ScienceOn
18 Ukkusuri, S. V. and Yushimito, W. F. (2008), Location routing approach for the humanitarian prepositioning problem, Transportation Research Record: Journal of the Transportation Research Board, 2089(1), 18-25.   DOI
19 Van Wassenhove, L. N. (2006), Humanitarian aid logistics: supply chain management in high gear, Journal of the Operational Research Society, 57(5), 475-489.   DOI   ScienceOn
20 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.   DOI   ScienceOn
21 Gunnec, D. and Salman, F. S. (2007), A two-stage multi-criteria stochastic programming model for location of emergency response and distribution centers, Proceedings of the International Network Optimization Conference (INOC), Spa, Belgium, 1-6.