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Uncertainty in Humanitarian Logistics for Disaster Management. A Review

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Decision Aid Models for Disaster Management and Emergencies

Part of the book series: Atlantis Computational Intelligence Systems ((ATLANTISCIS,volume 7))

Abstract

 Given their nature, disasters are generally characterized by a high level of uncertainty. In fact, both their occurrence and their consequences are not easily anticipated. Thus, NGOs and civil protection often have to take decisions and plan for their operations without having the possibility of relying on exact or complete information on the magnitude of the disaster. Over the years, a number of works and methodologies that address uncertainty in Disaster Management have been presented in the literature. In this chapter we review different forms of tackling uncertainty in Humanitarian Logistics for Disaster Management and propose a classification of the advances in this research field.

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References

  1. Adivar B., Mert A. (2010). International disaster relief planning with fuzzy credibility. Fuzzy Optimization and Decision Making, Vol. 9, pp. 413–433.

    Google Scholar 

  2. Altay N., Green W. G. (2006). OR/MS research in disaster operations management. European Journal of Operational Research, Vol. 175, pp. 475–493.

    Google Scholar 

  3. Bakuli D. L., MacGregor Smith J. (1996). Resource allocation in state-dependent emergency evacuation networks. European Journal of Operational Research, Vol. 89, pp. 543–555.

    Google Scholar 

  4. Balcik B., Beamon B. M. (2008). Facility location in humanitarian relief. International Journal of Logistics: Research and Applications, Vol. 11 (2), pp. 101–121.

    Google Scholar 

  5. Barbarosoglu G., Arda Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research Society, Vol. 55, pp. 43–53. November 27, 2012 23:14 Atlantis Press Book - 9.75in x 6.5in book_Vitoriano-Montero Bibliography 73.

    Google Scholar 

  6. Belardo S., Harrald J., Wallace W.A., Ward J. (1984). A partial covering approach to sitting response resources for major maritime oil spills. Management Science, Vol. 30 (10), pp. 1184–1196.

    Google Scholar 

  7. 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, Vol. 45, pp. 1177–1189.

    Google Scholar 

  8. Caunhye A.M., Niea X., Pokharelb S. (2011). Optimization models in emergency logistics: A literature review. Socio-Economic Planning Sciences, Vol. 46 (1), pp. 4–13.

    Google Scholar 

  9. Chan Y., Carter W. B., Burnes M. D. (2001). A multiple-depot, multiple-vehicle, locationrouting problem with stochastically processed demands. Computers & Operations Research, Vol. 28, pp. 803–826.

    Google Scholar 

  10. Chang MS., Tseng YL., Chen JW. (2007). A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transportation Research Part E: Logistics and Transportation Review, Vol. 43 (6), pp. 737–754.

    Google Scholar 

  11. Clarke G., Wright J.W. (1964). Scheduling of Vehicles from a Central Depot to a Number of Delivery Points. Operations Research, Vol. 12, pp. 568–581.

    Google Scholar 

  12. De la Torre L.E., Dolinskaya I.S., Smilowitz K.R. (2012). Disaster Relief Routing: Integrating Research and Practice. Socio-Economic Planning Sciences, Vol. 46 (1), pp. 88–97.

    Google Scholar 

  13. Deb, K., Gupta, H. (2006) Introducing robustness in multi-objective optimization, Evolutionary Computation 14 (4) pp 463–494.

    Google Scholar 

  14. Dilley, M., Chen, R. S., Deichmann, U., Lerner-Lam, A.L., Arnold, M., Agwe, J., Buys, P., Kjekstad, O., Lyon, B. and Yetman, G. 2005. Natural disaster hotspots: a global risk analysis. Synthesis report.

    Google Scholar 

  15. Duran S, Gutierrez MA, Keskinocak PN. (2011). Pre-positioning of emergency items worldwide for CARE international. Interfaces, Vol. 41 (3), pp. 223–237.

    Google Scholar 

  16. Fiedrich F., Gehbauer F., Rickers U. (2000). Optimized resource allocation for emergency response after earthquake disasters. Safety Science, Vol. 35 (1-3), pp. 41–57.

    Google Scholar 

  17. Günneç D., Salman F.S. (2011). Assessing the reliability and the expected performance of a network under disaster risk, OR Spectrum, Vol. 33, pp. 499–523.

    Google Scholar 

  18. Hentenryck P.V., Bent R., Coffrin C. (2010). Strategic Planning for Disaster Recovery with Stochastic Last Mile Distribution. Proceedings of the Seventh International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR 2010), pp. 318–333.

    Google Scholar 

  19. Huang Y., Fan Y., Cheu R.L. (2007). Optimal Allocation of Multiple Emergency Service Resources for Protection of Critical Transportation Infrastructure. Transportation Research Board, Vol. 2022, pp. 1–8.

    Google Scholar 

  20. Huang Y., Fan Y. (2011). Modeling Uncertainties in Emergency Service Resource Allocation. Journal of Infrastructure Systems, Vol. 17 (1), pp. 35–41.

    Google Scholar 

  21. Li L., Jin M., Zhang L. (2011). Sheltering network planning and management with a case in the Gulf Coast region. International Journal of Production Economics, Vol.131, pp.431–440.

    Google Scholar 

  22. Mete HO, Zabinsky ZB. (2010). Stochastic optimization of medical supply location and distribution in disaster management. International Journal of Production Economics, Vol. 126 (1), pp. 76–84.

    Google Scholar 

  23. Moss, R.H. and Schneider, S.H. (2000) Uncertainties in the IPCC TAR: Recommendations to lead authors for more consistent assessment and reporting. In: Guidance Papers on the Cross Cutting Issues of the Third Assessment Report of the IPCC [eds. R. Pachauri, T. Taniguchi and K. Tanaka], World Meteorological Organization, Geneva, pp. 33–51.

    Google Scholar 

  24. Nolz P.C., Semet F., Doerner K.F. (2011). Risk approaches for delivering disaster relief supplies, OR Spectrum, Vol. 33, pp. 543–569. November 27, 2012 23:14 Atlantis Press Book - 9.75in x 6.5in book_Vitoriano-Montero 74 Decision Aid Models for Disaster Management and Emergencies.

    Google Scholar 

  25. Noyan N. (2012). Risk-averse two-stage stochastic programming with an application to disaster management. Computers & Operations Research, Vol. 39, pp. 541–559.

    Google Scholar 

  26. Ortuño, M.T., Tirado, G., Vitoriano, B.: A lexicographical goal programming based decision support system for logistics of Humanitarian Aid. Top, Vol. 19 (2), pp. 646–679.

    Google Scholar 

  27. Pedraza-Martinez, A.J., Stapleton, O.,VanWassenhove, L.N. (2011) Field vehicle fleet management in humanitarian operations: A case-based approach. Journal of Operations Management, Vol. 29 (5), pp. 404–421.

    Google Scholar 

  28. Rawls CG, Turnquist MA. (2010). Pre-positioning of emergency supplies for disaster response. Transportation Research Part B: Methodological, Vol. 44 (4), pp. 521–34.

    Google Scholar 

  29. Rodriguez J.T., Vitoriano B., Montero J. (2010). A natural-disaster management DSS for Humanitarian Non-Governmental Organisations, Knowledge-Based Systems, Vol. 23, pp. 17–22.

    Google Scholar 

  30. [30] Rodriguez J.T., Vitoriano B., Montero J., Vojislav K. (2011). A disaster-severity assessment DSS comparative analysis, OR Spectrum, Vol. 33, pp. 451–479.

    Google Scholar 

  31. Rodriguez J.T., Vitoriano B., Montero J. (2012). A general methodology for data-based rule building and its application to natural disaster management, Computers & Operations Research, Vol. 39, pp. 863–873.

    Google Scholar 

  32. Rottkemper B., Fischer K., Blecken A., Danne C. (2011). Inventory relocation for overlapping disaster settings in humanitarian operations, OR Spectrum, Vol. 33, pp. 721–749.

    Google Scholar 

  33. Salmerón J., Apte A. (2010). Stochastic Optimization for Natural Disaster Asset Prepositioning. Production and operations management, Vol. 19 (5), pp. 561–574.

    Google Scholar 

  34. Shen Z., Dessouky M.M., Ordoñez F. (2009). A two-stage vehicle routing model for large-scale bioterrorism emergencies. Networks, Vol. 54 (4), pp. 255–269.

    Google Scholar 

  35. Sheu J.B. (2007). An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research Part E, Vol. 43 (6), pp. 687–709.

    Google Scholar 

  36. Sheu J.B. (2010). Dynamic relief-demand management for emergency logistics operations under large-scale disasters. Transportation Research Part E, Vol. 46, pp. 1–17.

    Google Scholar 

  37. Song R., He S., Zhang L. (2009). Optimum transit operations during the emergency evacuations. Journal of Transportation Systems Engineering and Information Technology, Vol. 9 (6), pp. 154–160. United Nations International Strategy for Disaster Reduction (UNISDR), (2009). Terminology on Disaster Risk Reduction. http://unisdr.org/files/ 7817_UNISDRTerminologyEnglish.pdf.

  38. Vitoriano B., Ortuño M.T., Tirado G., Montero J. (2011). A multi-criteria optimization model for humanitarian aid distribution, Journal of Global Optimization, Vol. 51, pp. 189–208.

    Google Scholar 

  39. Yazici M.A., Ozbay K. (2007). Impact of probabilistic road capacity constraints on the spatial distribution of hurricane evacuation shelter capacities. Transportation Research Record: Journal of the Transportation Research Board 2022, pp. 55–62.

    Google Scholar 

  40. Zadeh, L.A. (1965). Fuzzy sets. Information and Control 8 (3), pp. 338–353.

    Google Scholar 

  41. Zhu J., Huang J., Liu D., Han J. (2008). Resources Allocation Problem for Local Reserve Depots in DisasterManagement Based on Scenario Analysis. The 7th International Symposium on Operations Research and Its Applications (ISORA’08). ORSC & APORC, pp. 395–407.

    Google Scholar 

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Liberatore, F., Pizarro, C., de Blas, C.S., Ortuño, M.T., Vitoriano, B. (2013). Uncertainty in Humanitarian Logistics for Disaster Management. A Review. In: Vitoriano, B., Montero, J., Ruan, D. (eds) Decision Aid Models for Disaster Management and Emergencies. Atlantis Computational Intelligence Systems, vol 7. Atlantis Press, Paris. https://doi.org/10.2991/978-94-91216-74-9_3

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  • DOI: https://doi.org/10.2991/978-94-91216-74-9_3

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  • Online ISBN: 978-94-91216-74-9

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