A stochastic location and allocation model for critical items to response large-scale emergencies: A case of Turkey
DOI:
https://doi.org/10.11121/ijocta.01.2017.00300Keywords:
Emergency response, facility location, large scale emergencies, two stage stochastic programmingAbstract
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.
Downloads
References
Murali, P. Ordó-ez, F. & Dessouky, M.M., "Facility location under demand uncertainty: Response to a large-scale bio-terror attack", Socio-Economic Planning Sciences, vol. 46 No. 1, pp. 78-87(2012).
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).
Jia, H. Ordonez, F. & Dessouky, M., "A modeling framework for facility location of medical services for large-scale emergencies", IIE Transactions, Vol. 39 No. 1, pp. 41–55 (2007a).
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).
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).
Megiddo N. & Supowit K.J., "On the complexity of some common geometric location problems", SIAM Journal on Computing, Vol. 13, pp. 182-196 (1984).
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).
Birge, J.R. & Louveaux, F., "Introduction to stochastic programming", Springer-Verlag, New York (1997).
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).
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).
Balcik, B., & Beamon, B. M. "Facility location in humanitarian relief", International Journal of Logistics, Vol 11 No. 2, pp. 101-121 (2008).
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).
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).
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).
Toregas, C. Swain, R. ReVelle, C. & Bergman, L., "The location of emergency service facilities", Operations Research, Vol. 19 No. 6, pp. 1363-1373 (1971).
Psaraftis, H.N. Tharakan, G.G. & Ceder, A., "Optimal response to oil spills: the strategic decision case", Operations Research, Vol. 34 No. 2, pp. 203-217 (1986).
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).
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).
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).
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).
Duran, S. Gutierrez, M.A. & Keskinocak, P., "Pre-positioning of emergency items for care international", Interfaces, Vol. 41 No. 3, pp. 223-237 (2011).
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).
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).
Döyen, A. Aras, & N. Barbarosoğlu, G., "A two-echelon stochastic facility location model for humanitarian relief logistics", Optimization Letters, Vol. 6 No. 6, pp. 1123-1145 (2012).
Hong, X. Lejeune, M.A. & Noyan, N., "Stochastic Network Design for Disaster Preparedness", Optimization Online, pp. 1-31 (2012).
Salmerón, J. & Apte, A. (2010), "Stochastic optimization for natural disaster asset prepositioning", Production and Operations Management, Vol. 19 No. 5, pp. 561-574.
Lodree Jr, E.J. Ballard, K.N. & Song, C.H., "Pre-positioning hurricane supplies in a commercial supply chain", Socio-Economic Planning Sciences, Vol. 46 No.4, pp. 291-305 (2012).
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).
Yushimito, W.F. & Ukkusuri, S.V., "A Location-Routing Approach for the Humanitarian Pre-Positioning Problem", In 87th Annual Meeting of the Transportation Research Board, Washington, DC (2007).
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).
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).
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, Vol. 43 No. 6, pp.737-754 (2007).
Mete, H.O. & Zabinsky, Z.B., "Preparing for disasters: medical supply location and distribution", In Proceedings of the INFORMS conference, Seattle, WA, pp. 1-14 (2007).
Mete, H.O. & Zabinsky, Z.B., "Stochastic optimization of medical supply location and distribution in disaster management", International Journal of Production Economics, Vol. 126 No. 1, pp. 76-84 (2010).
Gunnec, D. & Salman, F., "A two-stage multi-criteria stochastic programming model for location of emergency response and distribution centers", In International Network Optimization Conference (2007).
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).
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).
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).
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).
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).
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).
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).
Rawls, C.G. & Turnquist, M.A., "Pre-positioning and dynamic delivery planning for short-term response following a natural disaster", Socio-Economic Planning Sciences, Vol. 46 No. 1, pp. 46-54 (2012).
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).
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).
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).
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).
Salman, F. S., & Gül, S., "Deployment of field hospitals in mass casualty incidents", Computers & Industrial Engineering, Vol 74, pp. 37-51 (2014).
Caunhye, A. M., Li, M., & Nie, X., "A location-allocation model for casualty response planning during catastrophic radiological incidents", Socio-Economic Planning Sciences, Vol 50, pp. 32-44 (2015).
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).
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).
Kılcı, F., Kara, B. Y., & Bozkaya, B., "Locating temporary shelter areas after an earthquake: A case for Turkey", European Journal of Operational Research, Vol 243 No. 1, pp. 323-332 (2015).
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).
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).
Sheu, J. B., "Dynamic relief-demand management for emergency logistics operations under large-scale disasters", Transportation Research Part E: Logistics and Transportation Review, Vol. 46 no. 1, pp. 1-17 (2010).
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).
Dantzig, G.B., "Planning under uncertainty", Annals of Operations Research, Vol. 85 pp.1-4, (1999).
Google maps [online]. Available from: https://maps.google.com. [accessed 16 September 2013].
TUIK [online]. Available from: http://www.tuik.gov.tr/UstMenu.do?metod=temelist. [accessed 13 September 2013].
Balcik, B. & Ak, D., "Supplier selection for framework agreements in humanitarian relief", Production and Operations Management, Vol. 23 No.6, pp.1028-1071 (2013).
KGM [online]. Available from: http://www.kgm.gov.tr/Sayfalar/KGM/SiteEng/Root/MainPageEnglish.aspx. Republic of Turkey General Directorate of Highways (KGM) [accessed 16 September 2013].
Downloads
Published
How to Cite
Issue
Section
License
Articles published in IJOCTA are made freely available online immediately upon publication, without subscription barriers to access. All articles published in this journal are licensed under the Creative Commons Attribution 4.0 International License (click here to read the full-text legal code). This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available.
Under the Creative Commons Attribution 4.0 International License, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles in IJOCTA, so long as the original authors and source are credited.
The readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material
- for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
This work is licensed under a Creative Commons Attribution 4.0 International License.
