Modelo de optimización para el diseño de redes de asistencia en catástrofe
DOI:
https://doi.org/10.17533/udea.redin.20241247Palabras clave:
Investigación de operaciones, modelos de programaci´n lineal entera mixta, Cadena de suministro humanitarioResumen
Se ha creado un modelo para optimizar las operaciones de ayudas humanitarias identificando la mejor ubicación para instalar los refugios. Este modelo, desarrollado mediante modelos de programación lineal entera mixta, tiene en cuenta la disponibilidad de recursos y el coste de las distintas ubicaciones, así como las restricciones que deben cumplirse para garantizar la entrega puntual del recurso. Se propuso una solución que implicaba el uso de un algoritmo de ramificación y corte, con la ayuda del API GeoJSON y Python. Además, se realizó un estudio para evaluar el impacto del modelo analizando el suministro de agua durante un desastre natural en Mocoa, Colombia, en 2017. Los resultados del estudio mostraron que el modelo tuvo un impacto positivo en la reducción de la distancia que debían recorrer los recursos, el aumento de la satisfacción de las necesidades de refugio y la disminución de los costes de implementación.
Descargas
Citas
B. S. Sahay, S. Gupta, and V. C. Menon, Managing Humanitarian Logistics, ser. Springer Proceedings in Business and Economics. New Delhi: Springer India, 2015.
C. Reis and T. Bernath, Becoming an International Humanitarian Aid Worker. Butterworth-Heinemann, 2017. [Online]. Available: https://doi.org/10.1016/B978-0-12-804314-1.00023
P. Tatham and M. Christopher, Humanitarian Logistics: Meeting the Challenge of Preparing For and Responding To Disasters, 3rd ed. London: Kogan Page, 2018.
OCHA, “The United Nations Office for the Coordination of Humanitarian Affairs. Global Humanitarian Overview 2018,” 2018.
G. Kovács, K. Spens, and M. Moshtari, The Palgrave Handbook of Humanitarian Logistics and Supply Chain Management. London: Palgrave Macmillan UK, 2017.
G. Kovács, K. Spens, and I. Haavisto, Supply Chain Management for Humanitarians: Tools for Practice, 1st ed. London: Kogan Page, 2016.
C. J. Chiappetta, V. A. Sobreiro, A. B. de Sousa, L. M. de Souza, E. B. Mariano, and D. W. S. Renwick, “An analysis of the literature on humanitarian logistics and supply chain management: paving the way for future studies,” Annals of Operations Research, Jun. 2017. [Online]. Available: https://doi.org/10.1007/s10479-017-2536-x
S. M. M. Daud, M. Hussein, M. Nasir, R. Abdullah, R. Kassim, M. Suliman, and M. R. Saludin, “Humanitarian logistics and its challenges: The literature review,” International Journal of Supply Chain Management, vol. 5, no. 3, 2016. [Online]. Available: https://core.ac.uk/download/pdf/230752814.pdf
N. Kunz, L. N. V. Wassenhove, M. Besiou, C. Hambye, and G. Kovács, “Relevance of humanitarian logistics research: best practices and way forward,” International Journal of Operations & Production Management, vol. 37, no. 11, 2017. [Online]. Available: https://doi.org/10.1108/IJOPM-04-2016-0202
A. Leiras, I. de Brito, E. Q. Peres, T. R. Bertazzo, and H. T. Y. Yoshizaki, “Literature review of humanitarian logistics research: trends and challenges,” Journal of Humanitarian Logistics and Supply Chain Management, vol. 4, no. 1, 2014. [Online]. Available: https://doi.org/10.1108/JHLSCM-04-2012-0008
M. T. E. Gutiérrez and J. E. S. Mutuc, “A model for humanitarian supply chain: An operation research approach,” Procedia Engineering, vol. 212, 2018. [Online]. Available: https://doi.org/10.1016/j.proeng.2018.01.085
Y. Chen, Q. Zhao, L. Wang, and M. Dessouky, “The regional cooperation-based warehouse location problem for relief supplies,” Computers & Industrial Engineering, vol. 102, 2016. [Online]. Available: https://doi.org/10.1016/j.cie.2016.10.021
R. Maharjan and S. Hanaoka, “Warehouse location determination for humanitarian relief distribution in Nepal,” Transportation Research Procedia, vol. 25, 2017. [Online]. Available: https://doi.org/10.1016/j.trpro.2017.05.128
N. Cotes and V. Cantillo, “Including deprivation costs in facility location models for humanitarian relief logistics,” Socio-Economic Planning Sciences, vol. 65, 2019. [Online]. Available: https://doi.org/10.1016/j.seps.2018.03.002
A. Verma and G. M. Gaukler, “Pre-positioning disaster response facilities at safe locations: An evaluation of deterministic and stochastic modeling approaches,” Computers Operations Research, vol. 62, 2015. [Online]. Available: https://doi.org/10.1016/j.cor.2014.10.006
O. B. Kınay, F. S. da Gama, and B. Y. Kara, “On multi-criteria chance-constrained capacitated single-source discrete facility location problems,” Omega, 2018. [Online]. Available: https://doi.org/10.1016/j.omega.2018.02.007
H. Yilmaz and O. Kabak, “A multiple objective mathematical program to determine locations of disaster response distribution centers,” IFAC-PapersOnLine, vol. 49, no. 12, 2016. [Online]. Available: https://doi.org/10.1016/j.ifacol.2016.07.682
W. J. Gutjahr and N. Dzubur, “Bi-objective bilevel optimization of distribution center locations considering user equilibria,” Transportation Research Part E: Logistics and Transportation Review, vol. 85, 2016. [Online]. Available: https://doi.org/10.1016/j.tre.2015.11.001
M. Haghi, S. M. T. F. Ghomi, and F. Jolai, “Developing a robust multi-objective model for pre/post disaster times under uncertainty in demand and resource,” Journal of Cleaner Production, vol. 154, 2017. [Online]. Available: https://doi.org/10.1016/j.jclepro.2017.03.102
Y. Liu, N. Cui, and J. Zhang, “Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service,” Transportation Research Part E: Logistics and Transportation Review, vol. 128, 2019. [Online]. Available: https://doi.org/10.1016/j.tre.2019.05.008
A. M. Paredes-Rodríguez, A. F. Toro-Pedroza, D. S. González-Tenorio, and J. T. Martínez-Ávila, “Stochastic linear programming model for the shelter’s location in small Colombian cities,” Revista Facultad de Ingeniería Universidad de Antioquia, 2024. [Online]. Available: https://doi.org/10.17533/udea.redin.20240619
J. A. Paul and L. MacDonald, “Location and capacity allocations decisions to mitigate the impacts of unexpected disasters,” European Journal of Operational Research, vol. 251, no. 1, 2016. [Online]. Available: https://doi.org/10.1016/j.ejor.2015.10.028
A. Charles, M. Lauras, L. N. V. Wassenhove, and L. Dupont, “Designing an efficient humanitarian supply network,” Journal of Operations Management, vol. 47–48, 2016. [Online]. Available: https://doi.org/10.1016/j.jom.2016.05.012
L. Muggy and J. L. H. Stamm, “Dynamic, robust models to quantify the impact of decentralization in post-disaster health care facility location decisions,” Operations Research for Health Care, vol. 12, 2017. [Online]. Available: https://doi.org/10.1016/j.orhc.2017.01.002
C. Boonmee, M. Arimura, and T. Asada, “Location and allocation optimization for integrated decisions on post-disaster waste supply chain management: On-site and off-site separation for recyclable materials,” International Journal of Disaster Risk Reduction, vol. 31, 2018. [Online]. Available: https://doi.org/10.1016/j.ijdrr.2018.07.003
N. Loree and F. Aros-Vera, “Points of distribution location and inventory management model for post-disaster humanitarian logistics,” Transportation Research Part E: Logistics and Transportation Review, vol. 116, 2018. [Online]. Available: https://doi.org/10.1016/j.tre.2018.05.003
A. Sebatli, F. Cavdur, and M. Kose-kucuk, “Determination of relief supplies demands and allocation of temporary disaster response facilities,” Transportation Research Procedia, vol. 22, 2017. [Online]. Available: https://doi.org/10.1016/j.trpro.2017.03.031
R. Mohammadi, S. M. T. F. Ghomi, and F. Jolai, “Prepositioning emergency earthquake response supplies: A new multi-objective particle swarm optimization algorithm,” Applied Mathematical Modelling, vol. 40, no. 9, 10, 2016. [Online]. Available: https://doi.org/10.1016/j.apm.2015.10.022
J. C. Smith, M. W. Horner, E. E. Ozguven, and A. Kocatepe, “How does accessibility to post-disaster relief compare between the aging and the general population? A spatial network optimization analysis of hurricane relief facility locations,” International Journal of Disaster Risk Reduction, vol. 15, 2016.
M. Zhao and X. Liu, “Development of decision support tool for optimizing urban emergency rescue facility locations to improve humanitarian logistics management,” Safety Science, vol. 102, 2018. [Online]. Available: https://doi.org/10.1016/j.ssci.2017.10.007
M. M. Farahani, S. K. Chaharsooghi, T. V. Woensel, and L. P. Veelenturf, “Capacitated network-flow approach to the evacuation-location problem,” Computers Industrial Engineering, vol. 115, 2018. [Online]. Available: https://doi.org/10.1016/j.cie.2017.11.026
L. de Oliveira-Silva, R. A. D. Mello-Bandeira, and V. B. Gouvea-Campos, “Proposal to planning facility location using UAV and geographic information systems in a post-disaster scenario,” International Journal of Disaster Risk Reduction, vol. 36, 2019. [Online]. Available: https://doi.org/10.1016/j.ijdrr.2019.101080
L. Cadarso, E. Codina, L. F. Escudero, and A. Marín, “Rapid transit network design: Considering recovery robustness and risk aversion measures,” Transportation Research Procedia, vol. 22, 2017. [Online]. Available: https://doi.org/10.1016/j.trpro.2017.03.032
S. Chopra and P. Meindl, Supply Chain Management: Strategy, Planning, and Operation, 6th ed. USA: Pearson Education, Jun. 2016.
J. Holguín-Veras, N. Pérez, M. Jaller, L. N. V. Wassenhove, and F. Aros-Vera, “On the appropriate objective function for post-disaster humanitarian logistics models,” Journal of Operations Management, vol. 31, no. 5, Jul. 2013. [Online]. Available: https://doi.org/10.1016/j.jom.2013.06.002
W. J. Gutjahr and S. Fischer, “Equity and deprivation costs in humanitarian logistics,” European Journal of Operational Research, vol. 270, no. 1, Oct. 2018. [Online]. Available: https://doi.org/10.1016/j.ejor.2018.03.019
G. LLC, Distance Matrix API: Developer Guide, 2017. [Online]. Available: https://developers.google.com/maps/documentation/distance-matrix
A. H. Land and A. G. Doig, “An automatic method for solving discrete programming problems,” in Years of Integer Programming 1958-2008, M. Junger, Ed. Berlin, Heidelberg: Springer, 210. [Online]. Available: https://doi.org/10.1007/978-3-540-68279-0_5
Hdx, Humanitarian Data Exchange. Colombia - Building Damage Assessment in the city of Mocoa, 2017. [Online]. Available: https://data.humdata.org/dataset/building-damage-assessment-in-the-city-of-mocoa-colombia
OCHA, The United Nations Office for the Coordination of Humanitarian Affairs, Colombia: Creciente súbita y deslizamientos en Mocoa, Putumayo. Reporte de Situación No. 03 (al 11.04.2017), 2017. [Online]. Available: https://tinyurl.com/2p99nvx4
OCHA, The United Nations Office for the Coordination of Humanitarian Affairs, Colombia – Avalancha e inundaciones en Mocoa (Putumayo). Flash Update No. 4 (04/04/17), 2017. [Online]. Available: https://tinyurl.com/972fprr9
OCHA, The United Nations Office for the Coordination of Humanitarian Affairs, Colombia: Putumayo - Mocoa Zonas de afectación (18/04/2017), 2017. [Online]. Available: https://www.unocha.org/publications/map/colombia/colombia-putumayo-mocoa-zonas-de-afectaci-n-18-04-2017
C. R. Colombiana, Manual Nacional para el manejo de Albergues Temporales. Bogotá: Sociedad Nacional de La Cruz Roja Colombiana: Dirección General del Socorro Nacional, Dec. 2008. [Online]. Available: https://reliefweb.int/report/colombia/manual-nacional-para-el-manejo-de-albergues-temporales
MinTransporte, Costos por movilización y por tiempo logístico, 2014. [Online]. Available: https://www.mintransporte.gov.co
ANI, Agencia Nacional de Infraestructura. Anexo Técnico No.1. Estudios y Documentos previos definitivo. Cotización Tanque y regador de agua, 2016.
L. Ding and N. Zhang, “A travel mode choice model using individual grouping based on cluster analysis,” Procedia Engineering, vol. 137, Feb. 10, 2016. [Online]. Available: https://doi.org/10.1016/j.proeng.2016.01.317
R. N. Rachmawati and N. H. Pusponegoro, “Hierarchical linear mixed model for poverty analysis in Indonesia,” Procedia Computer Science, vol. 116, 2017. [Online]. Available: https://doi.org/10.1016/j.procs.2017.10.071
N. H. Pusponegoro, R. N. Rachmawati, K. A. Notodiputro, and B. Sartono, “Linear mixed model for analyzing longitudinal data: A simulation study of children growth differences,” Procedia Computer Science, vol. 116, Oct. 13, 2017. [Online]. Available: https://doi.org/10.1016/j.procs.2017.10.071
W. Wang, W. Wang, T. H. Mosley, and M. E. Griswold, “A SAS macro for the joint modeling of longitudinal outcomes and multiple competing risk dropouts,” Computer Methods and Programs in Biomedicine, vol. 138, Jan. 2017. [Online]. Available: https://doi.org/10.1016/j.cmpb.2016.10.003
S. I. Inc, SAS/OR(R) 14.1 User’s Guide: Mathematical Programming - The Mixed Integer Linear Programming Solver, 2018. [Online]. Available: https://support.sas.com/documentation//cdl/en/ormpug/68156/HTML/default/viewer.htm#titlepage.htm
D.-S. Chen, R. G. Batson, and Y. Dang, Applied Integer Programming: Modeling and Solution. John Wiley & Sons, Dec. 2011.
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2024 Revista Facultad de Ingeniería Universidad de Antioquia
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Los artículos disponibles en la Revista Facultad de Ingeniería, Universidad de Antioquia están bajo la licencia Creative Commons Attribution BY-NC-SA 4.0.
Eres libre de:
Compartir — copiar y redistribuir el material en cualquier medio o formato
Adaptar : remezclar, transformar y construir sobre el material.
Bajo los siguientes términos:
Reconocimiento : debe otorgar el crédito correspondiente , proporcionar un enlace a la licencia e indicar si se realizaron cambios . Puede hacerlo de cualquier manera razonable, pero no de ninguna manera que sugiera que el licenciante lo respalda a usted o su uso.
No comercial : no puede utilizar el material con fines comerciales .
Compartir igual : si remezcla, transforma o construye a partir del material, debe distribuir sus contribuciones bajo la misma licencia que el original.
El material publicado por la revista puede ser distribuido, copiado y exhibido por terceros si se dan los respectivos créditos a la revista, sin ningún costo. No se puede obtener ningún beneficio comercial y las obras derivadas tienen que estar bajo los mismos términos de licencia que el trabajo original.