A stochastic location and allocation model for critical items to response large-scale emergencies: A case of Turkey
This paper aims to decide on the number of facilities and their locations, procurement for pre and post-disaster, and allocation to mitigate the effects of large-scale emergencies. A two-stage stochastic mixed integer programming model is proposed that combines facility location- prepositioning, decisions on pre-stocking levels for emergency supplies, and allocation of located distribution centers (DCs) to affected locations and distribution of those supplies to several demand locations after large-scale emergencies with uncertainty in demand. Also, the use of the model is demonstrated through a case study for prepositioning of supplies in probable large-scale emergencies in the eastern and southeastern Anatolian sides of Turkey. The results provide a framework for relief organizations to determine the location and number of DCs in different settings, by using the proposed model considering the main parameters, as; capacity of facilities, probability of being affected for each demand points, severity of events, maximum distance between a demand point and distribution center.
[1] Murali, P. Ordóñez, F. & Dessouky, M.M., “Facility location under demand uncertainty: Response to a large-scale bio-terror attack”, SocioEconomic Planning Sciences, vol. 46 No. 1, pp. 78- 87(2012).
[2] Sheu, J. B., “An emergency logistics distribution approach for quick response to urgent relief demand in disasters”, Transportation Research Part E: Logistics and Transportation Review, Vol. 43 No. 6, pp. 687-709 (2007).
[3] Jia, H. Ordonez, F. & Dessouky, M., “A modeling framework for facility location of medical services
[4] Jia, H. Ordonez, F. & Dessouky, M., “Solution approaches for facility location of medical supplies for large-scale emergencies”, Computers & Industrial Engineering, Vol. 52, pp. 257-276 (2007b).
[5] Rawls, C.G. & Turnquist, M.A., “Pre-positioning of emergency supplies for disaster response”, Transportation Research Part B: Methodological, Vol. 44 No. 4, pp. 521-534 (2010).
[6] Megiddo N. & Supowit K.J., “On the complexity of some common geometric location problems”, SIAM Journal on Computing, Vol. 13, pp. 182-196 (1984).
[7] Haugen, K.K. Løkketangen, A. & Woodruff, D.L., “Progressive hedging as a meta-heuristic applied to stochastic lot-sizing”, European Journal of Operational Research, Vol. 132 No. 1, pp. 116-122 (2001).
[8] Birge, J.R. & Louveaux, F., “Introduction to stochastic programming”, Springer-Verlag, New York (1997).
[9] Aydin, N., and Murat, A.. “A swarm intelligence based sample average approximation algorithm for the capacitated reliable facility location problem”, International Journal of Production Economics, Vol 145 No. 1, pp. 173-183 (2013).
[10] Ayvaz, B., Bolat, B., & Aydin, N.. “Stochastic reverse logistics network design for waste of electrical and electronic equipment”. Resources, Conservation and Recycling, Vol 104, pp. 391-404 (2015).
[11] Balcik, B., & Beamon, B. M.. “Facility location in humanitarian relief”, International Journal of Logistics, Vol 11 No. 2, pp. 101-121 (2008).
[12] Altay, N. Green, W.G., “OR/MS research in disaster operations management”, European Journal of Operational Research, Vol. 175 No.1, pp. 475-493 (2006).
[13] Galindo, G. & Batta, R., “Review of Recent Developments in OR/MS Research in Disaster Operations Management”, European Journal of Operational Research, Vol. 230 No. 2, pp. 201-211 (2013).
[14] Caunhye, A.M. Nie, X. & Pokharel, S., “Optimization models in emergency logistics: A literature review”, Socio-Economic Planning Sciences, Vol. 46 No. 1, pp.4-13 (2012).
[15] Toregas, C. Swain, R. ReVelle, C. & Bergman, L., “The location of emergency service facilities”, Operations Research, Vol. 19 No. 6, pp. 1363-1373 (1971).
[16] Psaraftis, H.N. Tharakan, G.G. & Ceder, A., “Optimal response to oil spills: the strategicdecision case”, Operations Research, Vol. 34 No. 2, pp. 203-217 (1986).
[17] Iakovou, E. Ip, C.M. Douligeris, C. & Korde, A., “Optimal location and capacity of emergency cleanup equipment for oil spill response”, European Journal of Operational Research, Vol. 96 No. 1, pp. 72-80 (1997).
[18] Huang, R. Kim, S. & Menezes, M.B., “Facility location for large-scale emergencies”, Annals of Operations Research, vol. 181 No. 1, pp. 271-286 (2010).
[19] Shui, W. Ye, H. Zhao, J. & Liu, M., “A Dynamic Multiple Objective Model of Location Problem of Emergency Logistics Distribution Centers”, Logistics, pp. 929-934 (2009).
[20] Yushimito, W.F. Jaller, M. & Ukkusuri, S., “A Voronoi-based heuristic algorithm for locating distribution centers in disasters”, Networks and Spatial Economics, Vol. 12 No. 1, pp. 21-39 (2012).
[21] Duran, S. Gutierrez, M.A. & Keskinocak, P., “Prepositioning of emergency items for care international”, Interfaces, Vol. 41 No. 3, pp. 223- 237 (2011).
[22] Rawls, C.G. & Turnquist, M.A., “Pre-positioning planning for emergency response with service quality constraints”, OR spectrum, Vol. 33 No. 3, pp. 481-498 (2011).
[23] Verma, A. & Gaukler, G.M., “A stochastic optimization model for positioning disaster response facilities for large-scale emergencies”, Network Optimization, Springer Berlin Heidelberg, pp. 547-552 (2011).
[24] Döyen, A. Aras, & N. Barbarosoğlu, G., “A twoechelon stochastic facility location model for humanitarian relief logistics”, Optimization Letters, Vol. 6 No. 6, pp. 1123-1145 (2012).
[25] Hong, X. Lejeune, M.A. & Noyan, N., “Stochastic Network Design for Disaster Preparedness”, Optimization Online, pp. 1-31 (2012).
[26] Salmerón, J. & Apte, A. (2010), “Stochastic optimization for natural disaster asset prepositioning”, Production and Operations Management, Vol. 19 No. 5, pp. 561-574.
[27] Lodree Jr, E.J. Ballard, K.N. & Song, C.H., “Prepositioning hurricane supplies in a commercial supply chain”, Socio-Economic Planning Sciences, Vol. 46 No.4, pp. 291-305 (2012).
[28] Campbell, A.M. & Jones, P.C., “Prepositioning supplies in preparation for disasters”, European Journal of Operational Research, Vol. 209 No.2, pp. 156-165 (2011).
[29] Yushimito, W.F. & Ukkusuri, S.V., “A LocationRouting Approach for the Humanitarian PrePositioning Problem”, In 87th Annual Meeting ofthe Transportation Research Board, Washington, DC (2007).
[30] Galindo, G. & Batta, R., “Prepositioning of supplies in preparation for a hurricane under potential destruction of prepositioned supplies”, Socio-Economic Planning Sciences, Vol. 47 No.1, pp. 20-37 (2012).
[31] Mitsakis, E. Stamos I. Salanova Grau J.M. & Aifadopoulou G., “Optimal allocation of emergency response services for managing disasters”, Disaster Prevention and Management, Vol. 23 No. 4, pp. 329 – 342 (2014).
[32] Chang, M.S. Tseng, Y.L. & Chen, J.W., “A scenario planning approach for the flood emergency logistics preparation problem under uncertainty”, Transportation Research Part E: Logistics and Transportation Review 6, pp.737-754 (2007). , Vol. 43 No.
[33] Mete, H.O. & Zabinsky, Z.B., “Preparing for disasters: medical supply location and distribution”, In Seattle, WA, pp. 1 Proceedings of the INFORMS conference -14 (2007). ,
[34] Mete, H.O. & Zabinsky, Z.B., “Stochastic optimization of medical supply location and distribution in disaster management”, International Journal of Production Economics pp. 76-84 (2010). , Vol. 126 No. 1,
[35] Gunnec, D. & Salman, F., “A two-stage multicriteria stochastic programming model for location of emergency response and distribution centers”, In International Network Optimization Conference(2007)
[36] Yi, W. Özdamar, L., “A dynamic logistics coordination model for evacuation and support in disaster response activities”, European Journal of Operational Research, Vol. 179 No. 3, pp. 1177- 1193 (2007).
[37] Han, Y., Guan, X., & Shi, L., “Optimization based method for supply location selection and routing in large-scale emergency material delivery”, IEEE Transactions on Automation Science and Engineering, Vol 8 No. 4, pp. 683-693 (2011).
[38] Bozorgi-Amiri, A. Jabalameli, M.S. Alinaghian, M. and Heydari, M., “A modified particle swarm optimization for disaster relief logistics under uncertain environment”, The International Journal of Advanced Manufacturing Technology, Vol. 60 No. 1-4, pp. 357-371 (2012).
[39] Naji-Azimi, Z., Renaud, J., Ruiz, A., & Salari, M.. “A covering tour approach to the location of satellite distribution centers to supply humanitarian aid”, European Journal of Operational Research, Vol 222 No. 3, pp. 596-605 (2012).
[40] Lin, Y.H. Batta, R. Rogerson, P.A. Blatt, A. & Flanigan, M., “Location of temporary depots to facilitate relief operations after an earthquake”,Socio-Economic Planning Sciences, Vol. 46 No. 2, pp. 112-123 (2012).
[41] Paul, J.A. & Hariharan, G., “Location-allocation planning of stockpiles for effective disaster mitigation”, Annals of Operations Research, Vol. 196 No. 1, pp. 469-490 (2012).
[42] Afshar, A., & Haghani, A., “Modeling integrated supply chain logistics in real-time large-scale disaster relief operations”, Socio-Economic Planning Sciences, Vol 46 No. 4, pp. 327-338 (2012).
[43] Rawls, C.G. & Turnquist, M.A., “Pre-positioning and dynamic delivery planning for short-term response following a natural disaster”, SocioEconomic Planning Sciences, Vol. 46 No. 1, pp. 46-54 (2012).
[44] Rath, S., & Gutjahr, W. J., “A math-heuristic for the warehouse location–routing problem in disaster relief”, Computers & Operations Research, Vol 42, pp. 25-39 (2014).
[45] Abounacer, R. Rekik, M. & Renaud, R., “An exact solution approach for multi-objective location– transportation problem for disaster response”, Computers & Operations Research, Vol. 41, pp. 83–93 (2014).
[46] Sheu, J. B., & Pan, C., “A method for designing centralized emergency supply network to respond to large-scale natural disasters”, Transportation Research Part B: Methodological, Vol 67, pp. 284- 305 (2014).
[47] Verma, A., & Gaukler, G. M., “Pre-positioning disaster response facilities at safe locations: An evaluation of deterministic and stochastic modeling approaches”, Computers & Operations Research, Vol 62, pp. 197-209 (2015).
[48] Salman, F. S., & Gül, S., “Deployment of field hospitals in mass casualty incidents”, Computers & Industrial Engineering, Vol 74, pp. 37-51 (2014).
[49] Caunhye, A. M., Li, M., & Nie, X., “A locationallocation model for casualty response planning during catastrophic radiological incidents”, SocioEconomic Planning Sciences, Vol 50, pp. 32-44 (2015).
[50] Renkli, Ç., & Duran, S., “Pre-positioning disaster response facilities and relief items”, Human and Ecological Risk Assessment: An International Journal, Vol 21 No. 5, pp. 1169-1185 (2015).
[51] Rath, S., Gendreau, M., & Gutjahr, W. J., “Bi‐ objective stochastic programming models for determining depot locations in disaster relief operations”, International Transactions in Operational Research, DOI: 10.1111/itor.12163 (2015).
[52] Kılcı, F., Kara, B. Y., & Bozkaya, B., “Locating temporary shelter areas after an earthquake: A casefor Turkey”, European Journal of Operational Research, Vol 243 No. 1, pp. 323-332 (2015).
[53] Aydin, N., “A stochastic mathematical model to locate field hospitals under disruption uncertainty for large-scale disaster preparedness”, An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Vol 6 No. 2, pp. 85-102 (2016).
[54] Tofighi, S., Torabi, S. A., & Mansouri, S. A., “Humanitarian logistics network design under mixed uncertainty”. European Journal of Operational Research, Vol. 250 No.1, pp. 239-250 (2016).
[55] Sheu, J. B., “Dynamic relief-demand management for emergency logistics operations under largescale disasters”, Transportation Research Part E: Logistics and Transportation Review, Vol. 46 no. 1, pp. 1-17 (2010).
[56] Chi, T.H. Yang, H. & Hsiao, H.M., “A new hierarchical facility location model and genetic algorithm for humanitarian relief”, 5th International Conference on New Trends in Information Science and Service Science (NISS) IEEE, Vol. 2, pp. 367-374 (2011).
[57] Dantzig, G.B., “Planning under uncertainty”, Annals of Operations Research, Vol. 85 pp.1-4, (1999).
[58] Google maps [online]. Available from: https://maps.google.com. [accessed 16 September 2013].
[59] TUIK [online]. Available from: http://www.tuik.gov.tr/UstMenu.do?metod=temelis t. [accessed 13 September 2013].
[60] Balcik, B. & Ak, D., “Supplier selection for framework agreements in humanitarian relief”, Production and Operations Management, Vol. 23 No.6, pp.1028-1071 (2013).
[61] KGM [online]. Available from: http://www.kgm.gov.tr/Sayfalar/KGM/SiteEng/Roo t/MainPageEnglish.aspx. Republic of TurkeyGeneral Directorate of Highways (KGM) [accessed 16 September 2013].