Developing Forecasting Tool for Humanitarian Relief Organizations in Emergency Logistics Planning
Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability distributions. The estimates of the parameters are used to calculate natural disaster forecasts. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.
[1] Altay, Altay, N., and Green, W. G., 2006. OR/MS research in disaster
operations management. European Journal of Operational Research,
175, p475-493.
[2] Ardekani S. A. and Hobeika A. (1988) Logistics problems in the
aftermath of the1985 Mexico City earthquake. Transportation Quarterly.
42(1), 107-124.
[3] Balcik, B. and Beamon, B. 2008. Facility location in humanitarian relief.
International Journal of Logistics: Research and Applications. Vol. 11,
No. 2, 101-121.
[4] Beamon, B., Humanitarian relief chains: Issues and challenges, in
Proceedings of the 34th International Conference on Computers and
Industrial Engineering, San Francisco, CA, 2004.
[5] Beamon, B. and Kotleba, S., Inventory Modeling for complex
emergencies in humanitarian relief operations. International Journal of
Logistics. Vol. 9, No. 1, March 2006, 1-18.
[6] Ben-Tal, A., Chung, B.D., Mandala, S.R., Yao,T. (2011). Robust optimization for emergency logistics planning: Risk mitigation in
humanitarian relief supply chains. Transportation Research Part B.
[7] Chang, M.S., Chen, S.R. and Hsueh, C.F., (2003), "Real-time vehicle
routing problem with time windows and simultaneous delivery/pickup demands," Journal of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 2273-2286.
[8] Chen, H.K., C.F. Hsueh and M.S. Chang, 2006, "The real-time timedependent
vehicle routing problem," Transportation Research Part E.
(Accepted)
[9] Doocy, S., Sirois, A., Anderson, J. (2011). Food security and
humanitarian assistance among displaced Iraqi populations in Jordan and
Syria. Social Science & Medicine, 72(2), 273-282.
[10] Dror, M., Trudeau, P., 1989. Savings by split delivery routing.
Transportation Science 23, 141-149.
[11] Frizzell, P.W., Giffin, J.W., 1995. The split delivery vehicle scheduling
problem with time windows and grid network distances. Computers and
Operational Research 22, 655-667.
[12] Gendreau, M., Laporte, G., Vigo, D., 1999. Heuristics for the traveling
salesman problem with pickup and delivery. Computers and Operations
Research 26, 699-714.
[13] Golden, B.L., Baker, E.K., Alfaro, J.L., Schaffer, J.R., 1985. The vehicle
routing problem with backhauling: two approaches. In: Proceedings of
the Twenty-First Annual Meeting of the S.E. TIMS, Myrtle Beach, SC, USA.
[14] Guha-Sapir, D., Vos, F., Below, R., Ponserre, S., 2011. Annual Disaster
Statistical Review 2011, The numbers and trends, CRED, IRSS, Universite Catholique de Louvain, Brussels, Belgium.
[15] Haghani, A. and Oh, S.C., Formulation and solution of a multicommodity,
multimodal network flow model for disaster relief
operations. Transportation Research: Part A, Policy and Practice, 1996,
30(3), 231-250.
[16] Hu, Z.H., (2011). A container multimodal transportation scheduling
approach based on immune affinity model for emergency relief. Expert
Systems with Applications, 38(3), 2632-2639.
[17] Jahre, M., 2008, Researcher project: HUMLOG-NET - Humanitarian
Logistics Networks, Norway.
[18] Kemball-Cook, D., Stephenson, R. (1984), "Lessons in logistics from
Somalia", Disasters, Vol. 8, 57-66.
[19] Knott R. (1987) The logistics of bulk relief supplies. Disasters 11, 113-
115.
[20] Kontoravdis, G., Bard, J.F., 1995. A GRASP for the vehicle routing
problem with time windows. ORSA Journal on Computing 7, 10-23.
[21] Kovács, G. and Spens, K.M. 2006. Humanitarian logistics in disaster
relief operations. In Jahre, Marianne (ed.): Logistics in the New Valley.
CD-ROM Proceedings of the 18th Annual Conference for Nordic Researchers in Logistics, NOFOMA 2006, Oslo, Norway.
[22] Kumar, A. 1988. Reliability estimation using doubly censored field data.
PhD dissertation, Department of Industrial Engineering, Virginia Tech,
Blacksburg, Virginia, USA.
[23] Lodree, Emmett J., 2011. "Pre-storm emergency supplies inventory
planning", Journal of Humanitarian Logistics and Supply Chain Management, Vol. 1 Iss: 1, pp.50 - 77.
[24] Min, H., 1989. The multiple vehicle routing problem with simultaneous
delivery and pickup points. International Journal of Management
Science 3, 1-14.
[25] Nagy, G., Salhi, S., 2005. Heuristic algorithms for single and multidepot
vehicle routing problems with pickups and deliveries. European Journal of Operational Research 162, 126-141.
[26] Oloruntoba, R. and Gray, R., Humanitarian aid: an agile supply chain,
Supply Chain Management, 2006, 11(2), 115-120.
[27] Özdamar, L., Ekinci, E. and Küçükyazaci, B., 2004, "Emergency logistics planning in natural disasters," Annals of Operations Research,
Vol. 129, pp. 217-245.
[28] Tatham, P., Kova'cs, G., 2010. The application of ÔÇÿÔÇÿswift trust-- to humanitarian logistics. International Journal of Production Economics,
126(1),35-45.
[29] Thomas, A. (2003) Why logistics? Forced Migration Review, Vol. 18,
p.4.
[30] Thomas, A.S., Humanitarian logistics: enabling disaster response, Fritz
Institute, 2007.
[31] Thomas, A.S. and Kopczak. L.R., 2005.From logistics to supply chain
management: The path forward in the humanitarian sector. Fritz
Institute.
[32] Van Wassenhove, L.N., 2006. Humanitarian aid logistics: supply chain
management in high gear. Journal of Operational Research Society,
57(5), 475–489.
[33] Ye, Y., Liu, N., (2011). A Bayesian Group-Information-Updated
sequential approach for humanitarian logistics planning in natural
disasters, Report, Institution of Logistics and Decision Optimization,
School of Management, Zhejiang University, China.
[34] Yi, W. and Ozdamar, L., 2007. A dynamic logistics coordination model
for evacuation and support in disaster response activities. European
Journal of Operations Research, 179, 1177-1193.
[35] Yi, W. and Kumar, A., 2007. Ant colony optimization for disaster relief
operations. Transportation Research Part E, 43, 660-672.
[36] World Bank Report, 2012.
[1] Altay, Altay, N., and Green, W. G., 2006. OR/MS research in disaster
operations management. European Journal of Operational Research,
175, p475-493.
[2] Ardekani S. A. and Hobeika A. (1988) Logistics problems in the
aftermath of the1985 Mexico City earthquake. Transportation Quarterly.
42(1), 107-124.
[3] Balcik, B. and Beamon, B. 2008. Facility location in humanitarian relief.
International Journal of Logistics: Research and Applications. Vol. 11,
No. 2, 101-121.
[4] Beamon, B., Humanitarian relief chains: Issues and challenges, in
Proceedings of the 34th International Conference on Computers and
Industrial Engineering, San Francisco, CA, 2004.
[5] Beamon, B. and Kotleba, S., Inventory Modeling for complex
emergencies in humanitarian relief operations. International Journal of
Logistics. Vol. 9, No. 1, March 2006, 1-18.
[6] Ben-Tal, A., Chung, B.D., Mandala, S.R., Yao,T. (2011). Robust optimization for emergency logistics planning: Risk mitigation in
humanitarian relief supply chains. Transportation Research Part B.
[7] Chang, M.S., Chen, S.R. and Hsueh, C.F., (2003), "Real-time vehicle
routing problem with time windows and simultaneous delivery/pickup demands," Journal of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 2273-2286.
[8] Chen, H.K., C.F. Hsueh and M.S. Chang, 2006, "The real-time timedependent
vehicle routing problem," Transportation Research Part E.
(Accepted)
[9] Doocy, S., Sirois, A., Anderson, J. (2011). Food security and
humanitarian assistance among displaced Iraqi populations in Jordan and
Syria. Social Science & Medicine, 72(2), 273-282.
[10] Dror, M., Trudeau, P., 1989. Savings by split delivery routing.
Transportation Science 23, 141-149.
[11] Frizzell, P.W., Giffin, J.W., 1995. The split delivery vehicle scheduling
problem with time windows and grid network distances. Computers and
Operational Research 22, 655-667.
[12] Gendreau, M., Laporte, G., Vigo, D., 1999. Heuristics for the traveling
salesman problem with pickup and delivery. Computers and Operations
Research 26, 699-714.
[13] Golden, B.L., Baker, E.K., Alfaro, J.L., Schaffer, J.R., 1985. The vehicle
routing problem with backhauling: two approaches. In: Proceedings of
the Twenty-First Annual Meeting of the S.E. TIMS, Myrtle Beach, SC, USA.
[14] Guha-Sapir, D., Vos, F., Below, R., Ponserre, S., 2011. Annual Disaster
Statistical Review 2011, The numbers and trends, CRED, IRSS, Universite Catholique de Louvain, Brussels, Belgium.
[15] Haghani, A. and Oh, S.C., Formulation and solution of a multicommodity,
multimodal network flow model for disaster relief
operations. Transportation Research: Part A, Policy and Practice, 1996,
30(3), 231-250.
[16] Hu, Z.H., (2011). A container multimodal transportation scheduling
approach based on immune affinity model for emergency relief. Expert
Systems with Applications, 38(3), 2632-2639.
[17] Jahre, M., 2008, Researcher project: HUMLOG-NET - Humanitarian
Logistics Networks, Norway.
[18] Kemball-Cook, D., Stephenson, R. (1984), "Lessons in logistics from
Somalia", Disasters, Vol. 8, 57-66.
[19] Knott R. (1987) The logistics of bulk relief supplies. Disasters 11, 113-
115.
[20] Kontoravdis, G., Bard, J.F., 1995. A GRASP for the vehicle routing
problem with time windows. ORSA Journal on Computing 7, 10-23.
[21] Kovács, G. and Spens, K.M. 2006. Humanitarian logistics in disaster
relief operations. In Jahre, Marianne (ed.): Logistics in the New Valley.
CD-ROM Proceedings of the 18th Annual Conference for Nordic Researchers in Logistics, NOFOMA 2006, Oslo, Norway.
[22] Kumar, A. 1988. Reliability estimation using doubly censored field data.
PhD dissertation, Department of Industrial Engineering, Virginia Tech,
Blacksburg, Virginia, USA.
[23] Lodree, Emmett J., 2011. "Pre-storm emergency supplies inventory
planning", Journal of Humanitarian Logistics and Supply Chain Management, Vol. 1 Iss: 1, pp.50 - 77.
[24] Min, H., 1989. The multiple vehicle routing problem with simultaneous
delivery and pickup points. International Journal of Management
Science 3, 1-14.
[25] Nagy, G., Salhi, S., 2005. Heuristic algorithms for single and multidepot
vehicle routing problems with pickups and deliveries. European Journal of Operational Research 162, 126-141.
[26] Oloruntoba, R. and Gray, R., Humanitarian aid: an agile supply chain,
Supply Chain Management, 2006, 11(2), 115-120.
[27] Özdamar, L., Ekinci, E. and Küçükyazaci, B., 2004, "Emergency logistics planning in natural disasters," Annals of Operations Research,
Vol. 129, pp. 217-245.
[28] Tatham, P., Kova'cs, G., 2010. The application of ÔÇÿÔÇÿswift trust-- to humanitarian logistics. International Journal of Production Economics,
126(1),35-45.
[29] Thomas, A. (2003) Why logistics? Forced Migration Review, Vol. 18,
p.4.
[30] Thomas, A.S., Humanitarian logistics: enabling disaster response, Fritz
Institute, 2007.
[31] Thomas, A.S. and Kopczak. L.R., 2005.From logistics to supply chain
management: The path forward in the humanitarian sector. Fritz
Institute.
[32] Van Wassenhove, L.N., 2006. Humanitarian aid logistics: supply chain
management in high gear. Journal of Operational Research Society,
57(5), 475–489.
[33] Ye, Y., Liu, N., (2011). A Bayesian Group-Information-Updated
sequential approach for humanitarian logistics planning in natural
disasters, Report, Institution of Logistics and Decision Optimization,
School of Management, Zhejiang University, China.
[34] Yi, W. and Ozdamar, L., 2007. A dynamic logistics coordination model
for evacuation and support in disaster response activities. European
Journal of Operations Research, 179, 1177-1193.
[35] Yi, W. and Kumar, A., 2007. Ant colony optimization for disaster relief
operations. Transportation Research Part E, 43, 660-672.
[36] World Bank Report, 2012.
@article{"International Journal of Business, Human and Social Sciences:59571", author = "Arun Kumar and Yousef L. A. Latif and Fugen Daver", title = "Developing Forecasting Tool for Humanitarian Relief Organizations in Emergency Logistics Planning", abstract = "Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability distributions. The estimates of the parameters are used to calculate natural disaster forecasts. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.
", keywords = "Humanitarian logistics, relief agencies, probability distribution.", volume = "6", number = "11", pages = "3219-7", }
