AJOR  Vol.5 No.3 , May 2015
Applying Network Flow Optimization Techniques to Improve Relief Goods Transport Strategies under Emergency Situation
ABSTRACT
Given the seriously damaged emergency situation occurring after a large-scale natural disaster, a critical and important problem that needs to be solved urgently is how to distribute the necessary relief goods, such as drinking water, food, and medicine, to the damaged area and how to transport them corresponding to the actual supply and demand situation as quickly as possible. The existing infrastructure, such as traffic roads, bridges, buildings, and other facilities, may suffer from severe damage. Assuming uncertainty related with each road segment’s availability, we formulate a transshipment network flow optimization problem under various types of uncertain situations. In order to express the uncertainty regarding the availability of each road segment, we apply the Monte Carlo simulation technique to generate random networks following certain probability distribution conditions. Then, we solve the model to obtain an optimal transport strategy for the relief goods. Thus, we try to implement a necessary and desirable response strategy for managing emergency cases caused by, for example, various natural disasters. Our modeling approach was then applied to the actual road network in Sumatra Island in Indonesia in 2009, when a disastrous earthquake occurred to develop effective and efficient public policies for emergency situations.

Cite this paper
Parwanto, N. , Morohosi, H. and Oyama, T. (2015) Applying Network Flow Optimization Techniques to Improve Relief Goods Transport Strategies under Emergency Situation. American Journal of Operations Research, 5, 95-111. doi: 10.4236/ajor.2015.53009.
References
[1]   EM-DAT (2014) The OFDA/CRED International Disaster Database. Universite catholique de Louvain, Brussels. www.emdat.be

[2]   Parwanto, N.B. and Oyama, T. (2014) A Statistical Analysis and Comparison of Historical Earthquake and Tsunami Disasters in Japan and Indonesia. International Journal of Disaster Risk Reduction, 7, 122-141.
http://dx.doi.org/10.1016/j.ijdrr.2013.10.003

[3]   Jiang, Y., Yuan, Y, Huang, K. and Zhao, L. (2012) Logistics for Large-Scale Disaster Response: Achievements and Challenges. 45th Hawaii International Conference on System Sciences, Maui, 4-7 January 2012, 1277-1285.
http://dx.doi.org/10.1109/HICSS.2012.418

[4]   Kovacs, G. and Spens, K.M. (2007) Humanitarian Logistics in Disaster Relief Operations. International Journal of Physical Distribution & Logistics Management, 37, 99-114.
http://dx.doi.org/10.1108/09600030710734820

[5]   Liu, D., Han, J.Y. and Zhu, J.M. (2007) Vehicle Routing for Medical Supplies in Large-Scale Emergencies. The First International Symposium on Optimization and Systems Biology (OSB2007), Beijing, 8-10 August 2007, 412-419.
http://www.aporc.org/LNOR/7/OSB2007F47.pdf

[6]   Van Wassenhove, L.N. (2006) Humanitarian Aid Logistics: Supply Chain Management in High Gear. Journal of Operational Research Society, 57, 475-489.
http://dx.doi.org/10.1057/palgrave.jors.2602125

[7]   Altay, N. and Green, W.G. (2006) OR/MS Research in Disaster Operations Management. European Journal of Operational Research, 175, 475-493.
http://dx.doi.org/10.1016/j.ejor.2005.05.016

[8]   Ozdamar, L., Ediz, E. and Beste, K. (2004) Emergency Logistics Planning in Natural Disasters. Annals of Operations Research, 129, 217-245.
http://dx.doi.org/10.1023/B:ANOR.0000030690.27939.39

[9]   Haghani, A. and Oh, S.C. (1996) Formulation and Solution of a Multi-Commodity Multi-Modal Network Flow for Disaster Relief Operations. Transportation Research Part A: Policy and Practice, 30, 231-250.
http://dx.doi.org/10.1016/0965-8564(95)00020-8

[10]   Fiedrich, F., Gehbauer, F. and Rickers, U. (2000) Optimized Resource Allocation for Emergency Response after Earthquake Disasters. Safety Science, 35, 41-57.
http://dx.doi.org/10.1016/S0925-7535(00)00021-7

[11]   Lin, Y.H., Batta, R., Rogerson, P.A., Blatt, A. and Flanigan, M. (2009) Application of a Humanitarian Relief Logistics Model to an Earthquake Disaster.
http://www.acsu.buffalo.edu/~batta/TRB_Updated.pdf

[12]   Tzeng, G.H., Cheng, H.J. and Huang, T.D. (2007) Multi-Objective Optimal Planning for Designing Relief Delivery Systems. Transportation Research Part E, 43, 673-686.
http://dx.doi.org/10.1016/j.tre.2006.10.012

[13]   Vitoriano, B., Ortuno, M.T., Tirado, G. and Montero, J. (2011) A Multi-Criteria Optimization Model for Humanitarian Aid Distribution. Journal of Global Optimization, 51, 189-208.
http://dx.doi.org/10.1007/s10898-010-9603-z

[14]   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, 1177-1193.
http://dx.doi.org/10.1016/j.ejor.2005.03.077

[15]   Barbarosoglu, G. and Arda, Y. (2004) A Two-Stage Stochastic Programming Framework for Transportation Planning in Disaster Response. Journal of the Operational Research Society, 55, 43-53.
http://dx.doi.org/10.1057/palgrave.jors.2601652

[16]   Winston, W.L. (2003) Operations Research Applications and Algorithms. 4th Edition, Duxbury Press, California.

[17]   Herer, Y.T., Tzur, M. and Yuecesan, E. (2006) The Multilocation Transshipment Problem. IIE Transactions, 38, 185-200.
http://dx.doi.org/10.1080/07408170500434539

[18]   Rottkemper, B., Fischer, K. and Blecken, A. (2012) A Transshipment Model for Distribution and Inventory Relocation under Uncertainty in Humanitarian Operations. Socio-Economic Planning Sciences, 46, 98-109.
http://dx.doi.org/10.1016/j.seps.2011.09.003

[19]   West Sumatra and Jambi Natural Disasters: Damage, Loss and Preliminary Needs Assessment. 2009. A Joint Report by the BPNB, Bappenas, and the Provincial and District/City Governments of West Sumatra and Jambi and International Partners.

[20]   Sugimin, P. (2011) Lesson Learned: Rehabilitation and Reconstruction West Sumatra September 30th, 2009 Earthquake, Building Back Better. Gramedia Ltd. Printing Group, Jakarta.

 
 
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