Correo Electrónico
DNINFOA - SIA
Bibliotecas
Convocatorias
Identidad U.N.
Publicado
Localización de instalaciones en logística humanitaria: una revisión de la literatura y consideraciones para futuras investigaciones
Facility location in humanitarian logistics: a literature review and considerations for future research
DOI:
https://doi.org/10.15446/dyna.v91n232.111818Palabras clave:
logística humanitaria; localización de instalaciones; desastres naturales (es)humanitarian logistics; facility location; natural disasters (en)
Descargas
La localización de instalaciones en la logística humanitaria es un problema crucial ya afecta directamente a la capacidad de respuesta, eficiencia en la distribución y al rendimiento de las operaciones de ayuda, este problema se caracteriza por la incertidumbre de la información, la velocidad en la reacción, la falta de recursos y la variabilidad del entorno haciendo que se generen nuevos modelos que se puedan ajustar a la realidad. En esta revisión de literatura se analizaron investigaciones publicadas entre los años 2020 y 2022. Con base en los estudios revisados, estos prefieren ajustarse a la realidad utilizando límites de capacidad, modelos estocásticos, ubicaciones no predefinidas, funciones de privación y multiobjetivo en emergencias generadas por desastres naturales. Finalmente se debe de considerar en futuras investigaciones: el tipo de temporalidad de la instalación, el enrutamiento con sus restricciones, el uso de modelos más robustos y el tamaño de las instalaciones.
The location of facilities in humanitarian logistics is a crucial problem as it directly affects the responsiveness, efficiency in distribution and performance of aid operations, this problem is characterized by uncertainty of information, speed of reaction, lack of resources and variability of the environment making it necessary to generate new models that can be adjusted to reality. In this literature review, research published between 2020 and 2022 was analyzed. Based on the studies reviewed, they prefer to adjust to reality using capacity limits, stochastic models, non-predefined locations, deprivation and multi-objective functions in emergencies generated by natural disasters. Finally, the following should be considered in future research: the type of temporality of the facility, the routing with its restrictions, the use of more robust models and the size of the facilities.
Referencias
Balcik, B., and Beamon, B.M., Facility location in humanitarian relief. International Journal of Logistics Research and Applications, 11(2), pp. 101-121, 2008. DOI: https://doi.org/10.1080/13675560701561789. DOI: https://doi.org/10.1080/13675560701561789
Boonmee, C., Arimura, M., and Asada, T., Facility location optimization model for emergency humanitarian logistics. International Journal of Disaster Risk Reduction, 24, pp. 485-498, 2017. DOI: https://doi.org/10.1016/j.ijdrr.2017.01.017. DOI: https://doi.org/10.1016/j.ijdrr.2017.01.017
Boostani, A., Jolai, F., and Bozorgi-Amiri, A., Designing a sustainable humanitarian relief logistics model in pre- and postdisaster management. International Journal of Sustainable Transportation, 15(8), pp. 604-620, 2020. DOI: https://doi.org/10.1080/15568318.2020.1773975. DOI: https://doi.org/10.1080/15568318.2020.1773975
Bozorgi-Amiri, A., and Khorsi, M., A dynamic multi-objective location-routing model for relief logistic planning under uncertainty on demand, travel time, and cost parameters. The International Journal of Advanced Manufacturing Technology, 85(5-8), pp. 1633-1648, 2015. DOI: https://doi.org/10.1007/s00170-015-7923-3. DOI: https://doi.org/10.1007/s00170-015-7923-3
Cotes, N., and Cantillo, V., Including deprivation costs in facility location models for humanitarian relief logistics. Socio-Economic Planning Sciences, 65, pp. 89-100, 2019. DOI: https://doi.org/10.1016/j.seps.2018.03.002. DOI: https://doi.org/10.1016/j.seps.2018.03.002
Cozzolino, A., Humanitarian logistics and supply chain management. Humanitarian Logistics. Cross-Sector Cooperation in Disaster Relief Management. SpringerBriefs in Business, Ed., 2012, pp. 5-16. DOI: https://doi.org/10.1007/978-3-642-30186-5_2 DOI: https://doi.org/10.1007/978-3-642-30186-5_2
Gulzari, A., and Tarakci, H., A healthcare location-allocation model with an application of telemedicine for an earthquake response phase. International Journal of Disaster Risk Reduction, 55, art. 102100, 2021. DOI: https://doi.org/10.1016/j.ijdrr.2021.102100. DOI: https://doi.org/10.1016/j.ijdrr.2021.102100
Gutjahr, W.J., and Fischer, S., Equity and deprivation costs in humanitarian logistics. European Journal of Operational Research, 270(1), pp. 185-197, 2018. DOI: https://doi.org/10.1016/j.ejor.2018.03.019. DOI: https://doi.org/10.1016/j.ejor.2018.03.019
Haeri, A., Hosseini-Motlagh, S.M., Samani, M.R.G., and Rezaei, M., A bi-level programming approach for improving relief logistics operations: a real case in Kermanshah earthquake. Computers & Industrial Engineering, 145, art. 106532, 2020. DOI: https://doi.org/10.1016/j.cie.2020.106532. DOI: https://doi.org/10.1016/j.cie.2020.106532
Holguín‐Veras, J., Jaller, M., Van Wassenhove, L.N., Pérez, N. and Wachtendorf, T., On the unique features of post‐disaster humanitarian logistics. Journal of Operations Management, 30(7-8), pp. 494-506, 2012. DOI: https://doi.org/10.1016/j.jom.2012.08.003. DOI: https://doi.org/10.1016/j.jom.2012.08.003
Holguín‐Veras, J., Pérez, N., Jaller, M., Van Wassenhove, L.N. and Aros‐Vera, F., On the appropriate objective function for post‐disaster humanitarian logistics models. Journal of Operations Management, 31(5), pp. 262-280, 2013. DOI: https://doi.org/10.1016/j.jom.2013.06.002. DOI: https://doi.org/10.1016/j.jom.2013.06.002
Jiang, Z., and Ouyang, Y., Reliable location of first responder stations for cooperative response to disasters. Transportation Research Part B: Methodological, 149, pp. 20-32, 2021. DOI: https://doi.org/10.1016/j.trb.2021.04.004. DOI: https://doi.org/10.1016/j.trb.2021.04.004
Khodaee, V., Kayvanfar, V., and Haji, A., A humanitarian cold supply chain distribution model with equity consideration: the case of COVID-19 vaccine distribution in the European Union. Decision Analytics Journal, 4, art. 100126. 2022. DOI: https://doi.org/10.1016/j.dajour.2022.100126. DOI: https://doi.org/10.1016/j.dajour.2022.100126
Li, Q., Li, M., Gan, J., and Guo, C., A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information. International Transactions in Operational Research, 28(4), pp. 1864-1889, 2020. DOI: https://doi.org/10.1111/itor.12900. DOI: https://doi.org/10.1111/itor.12900
Liu, K., Liu, C., Xiang, X., and Tian, Z., Testing facility location and dynamic capacity planning for pandemics with demand uncertainty. European Journal of Operational Research, 304(1), pp. 150-168, 2023. DOI: https://doi.org/10.1016/j.ejor.2021.11.028. DOI: https://doi.org/10.1016/j.ejor.2021.11.028
Liu, K., Zhang, H., and Zhang, Z.H., The efficiency, equity and effectiveness of location strategies in humanitarian logistics: a robust chance-constrained approach. Transportation Research Part E: Logistics and Transportation Review, 156, art. 102521, 2021. DOI: https://doi.org/10.1016/j.tre.2021.102521. DOI: https://doi.org/10.1016/j.tre.2021.102521
Liu, Y., Yuan, Y., Shen, J. and Gao, W., Emergency response facility location in transportation networks: a literature review. Journal of Traffic and Transportation Engineering, 8(2), pp. 153-169, 2021. DOI: https://doi.org/10.1016/j.jtte.2021.03.001. DOI: https://doi.org/10.1016/j.jtte.2021.03.001
oree, N., and Aros-Vera, F., Points of distribution location and inventory management model for post-disaster humanitarian logistics. Transportation Research Part E: Logistics and Transportation Review, 116, pp. 1-24, 2018. DOI: https://doi.org/10.1016/j.tre.2018.05.003. DOI: https://doi.org/10.1016/j.tre.2018.05.003
Maharjan, R., and Hanaoka, S., A multi-actor multi-objective optimization approach for locating temporary logistics hubs during disaster response. Journal of Humanitarian Logistics and Supply Chain Management, 8(1), pp. 2-21, 2018. DOI: https://doi.org/10.1108/jhlscm-08-2017-0040. DOI: https://doi.org/10.1108/JHLSCM-08-2017-0040
Maharjan, R., and Hanaoka, S., A credibility-based multi-objective temporary logistics hub location-allocation model for relief supply and distribution under uncertainty. Socio-Economic Planning Sciences, 70, art. 100727, 2020. DOI: https://doi.org/10.1016/j.seps.2019.07.003. DOI: https://doi.org/10.1016/j.seps.2019.07.003
Ming, J., Richard, J.P.P., and Zhu, J., A facility location and allocation model for cooperative fire services. IEEE Access, 9, pp. 90908-90918. 2021. DOI: https://doi.org/10.1109/access.2021.3091481. DOI: https://doi.org/10.1109/ACCESS.2021.3091481
Mishra, M., Singh, S.P., and Gupta, M.P., Two phase algorithm for bi-objective relief distribution location problem. Annals of Operations Research. 2022. DOI: https://doi.org/10.1007/s10479-022-04751-y. DOI: https://doi.org/10.1007/s10479-022-04751-y
Mohri, S.S., Akbarzadeh, M., and Sayed-Matin, S.H., A Hybrid model for locating new emergency facilities to improve the coverage of the road crashes. Socio-Economic Planning Sciences, 69, art. 100683, 2020. DOI: https://doi.org/10.1016/j.seps.2019.01.005. DOI: https://doi.org/10.1016/j.seps.2019.01.005
Monzón, J., Liberatore, F., and Vitoriano, B., A Mathematical Pre-Disaster Model with Uncertainty and Multiple Criteria for Facility Location and Network Fortification. Mathematics, 8(4), art. 529, 2020. DOI: https://doi.org/10.3390/math8040529. DOI: https://doi.org/10.3390/math8040529
Mousavi, H., Darestani, S.A., and Azimi, P., An artificial neural network based mathematical model for a stochastic health care facility location problem. Health Care Management Science, 24(3), pp. 499-514. 2021. DOI: https://doi.org/10.1007/s10729-020-09533-1. DOI: https://doi.org/10.1007/s10729-020-09533-1
Nawazish, M., Padhi, S.S., and Edwin-Cheng, T., Stratified delivery aid plans for humanitarian aid distribution centre selection. Computers & Industrial Engineering, 171, art. 108451, 2022. DOI: https://doi.org/10.1016/j.cie.2022.108451. DOI: https://doi.org/10.1016/j.cie.2022.108451
Oksuz, M.K., and Satoglu, S.I., A two-stage stochastic model for location planning of temporary medical centers for disaster response. International Journal of Disaster Risk Reduction, 44, art. 101426, 2020. DOI: https://doi.org/10.1016/j.ijdrr.2019.101426. DOI: https://doi.org/10.1016/j.ijdrr.2019.101426
Patel, N., and Trivedi, S., Choosing optimal locations for temporary health care facilities during health crisis using binary integer programming. Sage Science Review of Applied Machine Learning, [online]. 3(2), pp. 1-20, 2020. Available at: https://journals.sagescience.org/index.php/ssraml/article/view/7.
Praneetpholkrang, P., Huynh, V.N., and Kanjanawattana, S., A multi-objective optimization model for shelter location-allocation in response to humanitarian relief logistics. The Asian Journal of Shipping and Logistics, 37(2), pp. 149-156, 2021. DOI: https://doi.org/10.1016/j.ajsl.2021.01.003. DOI: https://doi.org/10.1016/j.ajsl.2021.01.003
Shehadeh, K.S., and Tucker, E.L., Stochastic optimization models for location and inventory prepositioning of disaster relief supplies. Transportation Research Part C: Emerging Technologies, 144, art. 103871, 2022. DOI: https://doi.org/10.1016/j.trc.2022.103871. DOI: https://doi.org/10.1016/j.trc.2022.103871
Shu, J., Lv, W., and Na, Q., Humanitarian relief supply network design: expander graph based approach and a case study of 2013 Flood in Northeast China. Transportation Research Part E: Logistics and Transportation Review, 146, art. 102178, 2021. DOI: https://doi.org/10.1016/j.tre.2020.102178. DOI: https://doi.org/10.1016/j.tre.2020.102178
Sun, H., Li, J., Wang, T., and Xue, Y., A novel scenario-based robust bi-objective optimization model for humanitarian logistics network under risk of disruptions. Transportation Research Part E: Logistics and Transportation Review, 157, art. 102578, 2022. DOI: https://doi.org/10.1016/j.tre.2021.102578. DOI: https://doi.org/10.1016/j.tre.2021.102578
Sun, H., Wang, Y., and Xue, Y., A bi-objective robust optimization model for disaster response planning under uncertainties. Computers & Industrial Engineering, 155, art. 107213, 2021. DOI: https://doi.org/10.1016/j.cie.2021.107213. DOI: https://doi.org/10.1016/j.cie.2021.107213
Sun, Q., and Liu, S., Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm. Science Progress, 104(2), art. 003685042110162, 2021. DOI: https://doi.org/10.1177/00368504211016205. DOI: https://doi.org/10.1177/00368504211016205
Tofighi, S., Torabi, S., and Mansouri, S., Humanitarian logistics network design under mixed uncertainty. European Journal of Operational Research, 250(1), pp. 239-250, 2016. DOI: https://doi.org/10.1016/j.ejor.2015.08.059. DOI: https://doi.org/10.1016/j.ejor.2015.08.059
Wang, H., and Ma, X., Research on multiobjective location of urban emergency logistics under major emergencies. Mathematical Problems in Engineering, art. 5577797, 2021, DOI: https://doi.org/10.1155/2021/5577797 DOI: https://doi.org/10.1155/2021/5577797
Yang, Y., Yin, J., Ye, M., She, D., and Yu, J., Multi-coverage optimal location model for emergency medical service (EMS) facilities under various disaster scenarios: a case study of urban fluvial floods in the Minhang district of Shanghai, China. Natural Hazards and Earth System Sciences, 20(1), pp. 181-195, 2020. DOI: https://doi.org/10.5194/nhess-20-181-2020. DOI: https://doi.org/10.5194/nhess-20-181-2020
Yeh, C.H., and Chen, Y.R., Location model analysis of flood relief facilities: a case study of the Fazih River floodplain, Taiwan. Natural Hazards, 103(1), pp. 317-327, 2020. DOI: https://doi.org/10.1007/s11069-020-03989-8. DOI: https://doi.org/10.1007/s11069-020-03989-8
Yu, W., Reachability guarantee-based model for pre-positioning of emergency facilities under uncertain disaster damages. International Journal of Disaster Risk Reduction, 42, art. 101335, 2020. DOI: https://doi.org/10.1016/j.ijdrr.2019.101335. DOI: https://doi.org/10.1016/j.ijdrr.2019.101335
Yu, W., Pre-disaster location and storage model for emergency commodities considering both randomness and uncertainty. Safety Science, 141, art. 105330, 2021. DOI: https://doi.org/10.1016/j.ssci.2021.105330. DOI: https://doi.org/10.1016/j.ssci.2021.105330
Dönmez, Z., Kara, B.Y., Karsu, Z., and Saldanha-da-Gama, F., Humanitarian facility location under uncertainty: Critical review and future prospects. Omega, 102, art. 102393, 2021. DOI: https://doi.org/10.1016/j.omega.2021.102393. DOI: https://doi.org/10.1016/j.omega.2021.102393
Zhang, L., and Cui, N., Pre-positioning facility location and resource allocation in humanitarian relief operations considering deprivation costs. Sustainability, 13(8), art. 4141, 2021. DOI: https://doi.org/10.3390/su13084141. DOI: https://doi.org/10.3390/su13084141
Cómo citar
IEEE
ACM
ACS
APA
ABNT
Chicago
Harvard
MLA
Turabian
Vancouver
Descargar cita
Licencia
Derechos de autor 2024 DYNA
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
El autor o autores de un artículo aceptado para publicación en cualquiera de las revistas editadas por la facultad de Minas cederán la totalidad de los derechos patrimoniales a la Universidad Nacional de Colombia de manera gratuita, dentro de los cuáles se incluyen: el derecho a editar, publicar, reproducir y distribuir tanto en medios impresos como digitales, además de incluir en artículo en índices internacionales y/o bases de datos, de igual manera, se faculta a la editorial para utilizar las imágenes, tablas y/o cualquier material gráfico presentado en el artículo para el diseño de carátulas o posters de la misma revista.
