Abstract
During the last decade, funds to face humanitarian operations have increased approximately ten times. According to the Global Humanitarian Assistance Report, in 2013 the humanitarian funding requirement was by US$ 22 billion, which represents \(27.2\%\) more than the requested in 2012. Furthermore, the transportation cost represents between one-third to two-thirds from the total logistics cost. Therefore, a frequent problem in a disaster relief is to reduce the transportation cost by keeping an adequate distribution service. The latter depends on a reliable delivery route design, which is not easy to do considering a post-disaster environment, where the infrastructures and sources could be inexistent, unavailable or inoperative. This paper tackles this problem, regarding the constraints, to deliver relief aids in a post-disaster state (like an eight-degree earthquake) in the capital of Perú. The routes found by the hierarchical ascending clustering approach, solved with a heuristic model, achieved a sufficient and satisfactory solution.
Keywords
- Vehicle Route Problem
- Transportation Time
- Vehicle Route
- Real Distance
- Travel Salesperson Problem
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Assessment, U.N.D., Coordination: Field handbook: UNDAC (2006)
Beamon, B.M., Balcik, B.: Performance measurement in humanitarian relief chains. Int. J. Public Sect. Manag. 21(1), 4–25 (2008)
Clarke, G., Wright, J.W.: Scheduling of vehicles from a central depot to a number of delivery points. Oper. Res. 12(4), 568–581 (1964)
Gong, Q., Batta, R.: Allocation and reallocation of ambulances to casualty clusters in a disaster relief operation. IIE Trans. 39(1), 27–39 (2007)
Hall, M.: Supply chain management in the humanitarian context: anatomy of effective relief and development chains. Master thesis, Webster University (2012)
Justel, A.: Técnicas de análisis multivariante para agrupación: Métodos cluster (2008)
Klibi, W., Martel, A.: Modeling approaches for the design of resilient supply networks under disruptions. Int. J. Prod. Econ. 135(2), 882–898 (2012)
Leseure, M., Hudson-Smith, M., Chandes, J., Paché, G.: Investigating humanitarian logistics issues: from operations management to strategic action. J. Manuf. Technol. Manag. 21(3), 320–340 (2010)
Martinez, A.J.P., Stapleton, O., Van Wassenhove, L.N.: Field vehicle fleet management in humanitarian operations: a case-based approach (2011)
Matthew, A., Elliott, R.J., Toshihiro, O., Strobl, E.: Natural disasters, industrial clusters and manufacturing plant survival (2015)
Özdamar, L., Demir, O.: A hierarchical clustering and routing procedure for large scale disaster relief logistics planning. Transp. Res. Part E Logist. Transp. Rev. 48(3), 591–602 (2012)
Pidd, M., De Silva, F., Eglese, R.: A simulation model for emergency evacuation. Eur. J. Oper. Res. 90(3), 413–419 (1996)
Prins, C., Lacomme, P., Prodhon, C.: Order-first split-second methods for vehicle routing problems: a review. Transp. Res. Part C Emerg. Technol. 40, 179–200 (2014)
Serpa Oshiro, V.R.: Optimización y localización de almacenes de abastecimiento para la atención de un terremoto de gran magnitud en lima metropolitana y callao (2014)
Tai, C.A., Lee, Y.L., Lin, C.Y.: Urban disaster prevention shelter location and evacuation behavior analysis. J. Asian Archit. Build. Eng. 9(1), 215–220 (2010)
Thevenaz, C., Resodihardjo, S.L.: All the best laid plans\(\ldots \) conditions impeding proper emergency response. Int. J. Prod. Econ. 126(1), 7–21 (2010)
Toth, P., Vigo, D.: The Vehicle Routing Problem. Monographs on Discrete Mathematics and Applications. Society for Industrial and Applied Mathematics, Philadelphia (2002)
Villardón, J.L.V.: Introducción al análisis de clúster. Departamento de Estadística, Universidad de Salamanca. p. 22 (2007)
Acknowledgement
The authors are grateful to the Research Group on Crisis and Disaster Management (CID) of the Pontificia Universidad Católica del Perú, for their valuable support and collaboration to this research work.
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Vargas-Florez, J., Medina-Rodríguez, R., Alva-Cabrera, R. (2017). A Clustering Optimization Approach for Disaster Relief Delivery: A Case Study in Lima-Perú. In: Lossio-Ventura, J., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig SIMBig 2015 2016. Communications in Computer and Information Science, vol 656. Springer, Cham. https://doi.org/10.1007/978-3-319-55209-5_6
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DOI: https://doi.org/10.1007/978-3-319-55209-5_6
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