Humanitarian Logistics Management After A Disaster: An Earthquake Case

Yıl 2020, , 679 - 688, 15.06.2020

Elifcan Göçmen , Yusuf Kuvvetli

https://doi.org/10.24012/dumf.658184

Cited By: 1

Öz

Post-disaster relief logistics includes logistics activities in the shortest time. Inventory routing problems have decided routing decisions considering inventory levels during the planning horizon at minimum cost. In this study, an inventory routing problem for the distribution after the disaster has been proposed. The problem aims the distribution of the supplies needed considering available inventory levels at minimum time. Distribution amount and the routes under the constraints of routing and inventory amounts for affected people have been decided. An integer programming approach to solve the problem has been proposed and solved. The proposed model is solved for a case of Van earthquake which occurred at 2011 in Turkey. The results from the case study show us that determining the inventory and routing decisions simultaneously can provide less logistic activities. In addition to this, holding inventory in the central depot can ensure to respond the emergency needs safely and quickly.

Anahtar Kelimeler

Post-disaster relief logistics, , Inventory-routing problems, Mathematical modelling

Kaynakça

• [1] Coelho, L.C.; Cordeau, J.F.; Laporte, G. Thirty years of inventory routing. Transportation science 2013, 48, 1-19.
• [2] Kovács, G.; Spens, K.M. Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution&Logistics Management 2007, 37, 99-114.
• [3] Sheu, J.B. An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transp. Res. Part E: Logist. Transp. Rev. 2007, 43, 687–709.
• [4] Balcik, B.; Beamon, B.M. Performance measurement in humanitarian relief chains. International Journal of Public Sector Management 2008, 21, 4-25.
• [5] Döyen, A.; Aras, N.; Barbarosoğlu, G. A two-echelon stochastic facility location model for humanitarian relief logistics. Optimization Letters 2012, 6, 1123-1145.
• [6] Mete, H.O.; Zabinsky, Z.B. Stochastic optimization of medical supply location and distribution in disaster management. International Journal of Production Economics 2010, 126, 76–84.
• [7] Duran, S.; Gutierrez, M.A.; Keskinocak, P. Pre-positioning of emergency items worldwide for care international. Forthcoming in Interfaces 2010, 41, 223-237.
• [8] Vahdani, B.; Veysmoradi, D.; Noori, F.; Mansour, F. Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty. International Journal of Disaster Risk Reduction 2018, 27, 290-306.
• [9]Ozdamar, L.; Ekinci, E.; Kucukyazici, B. Emergency logistics planning in natural disasters. Annals of Operations Research 2004, 129, 217-45.
• [10]Shen, Z.; Dessouky, M.; Ordonez, F. A two-stage vehicle routing model for large-scale bioterrorism emergencies. Networks 2009, 54, 255- 269.
• [11]Tofighi, S.; Torabi, S.A.; Mansouri, S.A. Humanitarian logistics network design under mixed uncertainty. European Journal Operation Research 2016, 250, 239–250.
• [12] Maghfiroh, M.F.N.; Hossain, M.; Hanaoka, S. Minimising emergency response time of ambulances through pre-positioning in dhaka city, bangladesh. International Journal of Logistics Research and Applications, 2017, 21, 53-71.
• [13] Noham, R.; Tzur, M. Designing humanitarian supply chains by incorporating actual post-disaster decisions. European Journal of Operational Research 2018, 265,1064-1077.
• [14] Hu, S.L.;. Han, C.F.; Meng, L.P. Stochastic optimization for joint decision making of inventory and procurement in humanitarian relief. Computer& Industrial Engineering 2017, 111, 39-49.
• [15] Samani, M.R.G.; Torabi, S.A.; Hosseini-Motlagh, S.M. Integrated blood supply chain planning for disaster relief. International Journal of Disaster Risk Reduction 2017, 27, 168-188,
• [16]Rodríguez-Espíndola, O.; Albores, P.; Brewster, C. Disaster preparedness in humanitarian logistics: a collaborative approach for resource management in floods. European Journal of Operational Research 2018, 264, 978–993.
• [17]Tavana, M.; Abtahic, A.R.; Di Caprio, D.; Hashemic, R.; Yousefi-Zenouzc, R. An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio-Economic Planning Sciences 2018.
• [18]Rezaei-Malek, M.; Tavakkoli-Moghaddam,R.; Zahiri, B.; Bozorgi-Amiri, A. An interactive approach for designing a robust disaster relief logistics network with perishable commodities. Comput Ind Eng 2016, 94, 201–215.
• [19]Zhu, C.; Fang, G.; Wang, O. Optimization on emergency resources transportation network based on bayes risk function: a case study. Math Probl Eng 2016.
• [20]Zhang, Y.; Qi, M.; Lin, W.H.; Miao, L. A meta-heuristic approach to the reliable location routing problem under disruptions. Transportation Research E Logistics Transport Rev 2015, 83, 90–110.
• [21] Bastian, N.D.; Griffin, P.M.; Spero, E.; Fulton, L.V. Multi-criteria logistics modeling for military humanitarian assistance and disaster relief aerial delivery operations. Optic Letters 2016, 10, 921–953.