dc.contributor | Cárdenas Aguirre, Diana María | |
dc.contributor | Meisel Donoso, José David | |
dc.creator | López Vargas, Juan Camilo | |
dc.date.accessioned | 2021-10-25T13:38:07Z | |
dc.date.accessioned | 2022-09-21T18:12:22Z | |
dc.date.available | 2021-10-25T13:38:07Z | |
dc.date.available | 2022-09-21T18:12:22Z | |
dc.date.created | 2021-10-25T13:38:07Z | |
dc.date.issued | 2021 | |
dc.identifier | https://repositorio.unal.edu.co/handle/unal/80604 | |
dc.identifier | Universidad Nacional de Colombia | |
dc.identifier | Repositorio Institucional Universidad Nacional de Colombia | |
dc.identifier | https://repositorio.unal.edu.co/ | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3406619 | |
dc.description.abstract | Ante los registros crecientes de desastres naturales acaecidos a nivel global, junto con otras amenazas que afronta la humanidad en la actualidad, como el aumento incontrolado de la población, los fenómenos de cambio climático, la seguridad alimentaria y la inequidad social, es necesario que desde el sector académico, y particularmente desde la Ingeniería, se aborden estas grandes problemáticas para formular alternativas de solución efectivas y sostenibles para el bienestar de las comunidades en condición de vulnerabilidad y la preservación de los ecosistemas en el mundo. Esta tesis se enmarca en el estudio de los procesos logísticos de preparación para la atención de emergencias y desastres a nivel local. El objetivo principal de la investigación es la formulación de distintos mecanismos de coordinación para que los actores locales clave puedan mejorar el desempeño global del sistema logístico durante los procesos de preparación para los desastres.
Para dicho propósito, fue necesario abordar un enfoque metodológico mixto que combinó prácticas tradicionalmente cualitativas como el estudio de expertos y un trabajo de campo basado en entrevistas semi-estrucutradas. Asimismo, desde el enfoque cuantitativo se aplicó el proceso de diseño para la estructuración y simulación de un modelo basado en agentes. Con base en un caso particular –la ciudad de Manizales, en Colombia–, se modelaron las principales decisiones que los actores del nivel local asumen en el marco de la preparación de emergencias causadas por fenómenos hidrometeorológicos. De este modo, y a partir de la formulación de escenarios alternativos basados en mecanismos de coordinación elegidos estratégicamente, se evidencia una mejora en el desempeño global del sistema local de preparación conformado por los principales actores locales. Los resultados obtenidos permiten vislumbrar una posibilidad de proponer e implementar mecanismos de coordinación en contextos reales, así como otras variantes en el modelo diseñado para dirigir futuras líneas de trabajo. | |
dc.description.abstract | Given the growing records of natural disasters that have occurred globally, as well as other threats that humanity endures, such as uncontrolled population growth, climate change, food security and social inequity, it is necessary to address these great problems from the academic sector, and particularly from Engineering, with the aim to formulate effective and sustainable solutions for the well-being of vulnerable communities and the preservation of ecosystems in the world. This thesis is focused on the study of the preparedness logistical processes for emergency and disaster response at the local level. The main research objective is the formulation of coordination mechanisms so that key local actors can improve the overall performance of the logistics system during disaster preparedness processes.
For this purpose, it was necessary to apply a mixed methodological approach that combined traditionally qualitative practices such as the study of experts and a field work based on semi-structured interviews. Likewise, from the quantitative approach, the design process was applied for the structuring and simulation of an agent-based model. Based on a particular case –the city of Manizales, in Colombia–, the main decisions that local actors take during preparedness stage for emergencies caused by hydrometeorological phenomena were modeled. Thus, and from the formulation of alternative scenarios based on strategically chosen coordination mechanisms, there is evidence of an improvement in the overall performance of the local preparedness system composed of the key local actors. The results obtained allow for the visualization of the possibility of proposing and implementing coordination mechanisms in real contexts, as well as other variants in the model designed to direct future lines of work. | |
dc.language | spa | |
dc.publisher | Universidad Nacional de Colombia | |
dc.publisher | Manizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - Industria y Organizaciones | |
dc.publisher | Departamento de Ingeniería Industrial | |
dc.publisher | Facultad de Ingeniería y Arquitectura | |
dc.publisher | Manizales, Colombia | |
dc.publisher | Universidad Nacional de Colombia - Sede Manizales | |
dc.relation | Abidi, H., & Scholten, K. (2015). Applicability of Performance Measurement Systems to Humanitarian Supply Chains. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 235-260. Doi: https://doi.org/10.1007/978-3-319-15455-8_13 | |
dc.relation | Acimovic, J., & Goentzel, J. (2016). Models and metrics to assess humanitarian response capacity. Journal of Operations Management, 45, 11-29. Doi: https://doi.org/10.1016/j.jom.2016.05.003 | |
dc.relation | Afsar, H. M., Prins, C., & Santos, A. C. (2014). Exact and heuristic algorithms for solving the generalized vehicle routing problem with flexible fleet size. International Transactions in Operational Research, 21 (1), 153-175. Doi: https://doi.org/10.1111/itor.12041 | |
dc.relation | Afshar, A., & Haghani, A. (2012). Modeling integrated supply chain logistics in real-time large-scale disaster relief operations. Socio-Economic Planning Sciences, 46 (4), 327-338. Doi: https://doi.org/10.1016/j.seps.2011.12.003 | |
dc.relation | Akhtar, P., Marr, N. E., & Garnevska, E. V. (2012). Coordination in humanitarian relief chains: chain coordinators. Journal of Humanitarian Logistics and Supply Chain Management, 2 (1), 85-103. Doi: https://doi.org/10.1108/20426741211226019 | |
dc.relation | Aksu, D. T., & Ozdamar, L. (2014). A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation. Transportation Research Part E: Logistics and Transportation Review, 61, 56-67. Doi: https://doi.org/10.1016/j.tre.2013.10.009 | |
dc.relation | Allen, T. T. (2011). Introduction to Discrete Event Simulation and Agent-based Modeling: Voting Systems, Health Care, Military, and Manufacturing. Londres: Springer. | |
dc.relation | Altay, N., & Green, W. G. (2006). OR/MS research in disaster operations management. European Journal of Operational Research, 175 (1), 475–493. Doi: https://doi.org/10.1016/j.ejor.2005.05.016 | |
dc.relation | Altay, N., & Pal, R. (2014). Information Diffusion among Agents: Implications for Humanitarian Operations. Production and Operations Management, 23 (6), 1015-1027. Doi: https://doi.org/10.1111/poms.12102 | |
dc.relation | Anaya-Arenas, A. M., Renaud, J., & Ruiz, A. (2014). Relief distribution networks: a systematic review. Annals of Operations Research, 223 (1), 53-79. Doi: https://doi.org/10.1007/s10479-014-1581-y | |
dc.relation | Anjomshoae, A., Hassan, A., Kunz, N., Wong, K. Y., & de Leeuw, S. (2017). Toward a dynamic balanced scorecard model for humanitarian relief organizations’ performance management. Journal of Humanitarian Logistics and Supply Chain Management, 7 (2), 194-218. Doi: https://doi.org/10.1108/JHLSCM-01-2017-0001 | |
dc.relation | Arnette, A. N., & Zobel, C. W. (2019). A Risk-Based Approach to Improving Disaster Relief Asset Pre-Positioning. Production and Operations Management, 28 (2), 457-478. Doi: https://doi.org/10.1111/poms.12934 | |
dc.relation | Aros, S. K., & Gibbons, D. E. (2018). Exploring communication media options in an inter-organizational disaster response coordination network using agent-based simulation. European Journal of Operational Research, 269 (2), 451-465. Doi: https://doi.org/10.1016/j.ejor.2018.02.013 | |
dc.relation | Bae, J. W., Shin, K., Lee, H. R., Lee, H. J., Lee, T., Kim, C. H., Cha, W. C., Kim, G. W., & Moon, I. C. (2018). Evaluation of Disaster Response System Using Agent-Based Model With Geospatial and Medical Details. IEEE Transactions on Systems Man Cybernetics-Systems, 48 (9), 1454-1469. Doi: https://doi.org/10.1109/TSMC.2017.2671340 | |
dc.relation | Balcik, B., & Beamon, B. M. (2008). Facility location in humanitarian relief. International Journal of Logistics: Research and Applications, 11 (2), 101-121. Doi: https://doi.org/10.1080/13675560701561789 | |
dc.relation | Balcik, B., Beamon, B. M., Krejci, C. C., Muramatsu, K. M., & Ramirez, M. (2010). Coordination in humanitarian relief chains: Practices, challenges and opportunities. International Journal of Production Economics, 126 (1), 22-34. Doi: https://doi.org/10.1016/j.ijpe.2009.09.008 | |
dc.relation | Baldini, G., Oliveri, F., Braun, M., Seuschek, H., & Hess, E. (2012). Securing disaster supply chains with cryptography enhanced RFID. Disaster Prevention and Management: An International Journal, 21 (1), 51-70. Doi: https://doi.org/10.1108/09653561211202700 | |
dc.relation | Banco Mundial. (2012). Análisis de la gestión del riesgo de desastres en Colombia: un aporte para la construcción de políticas públicas. Banco Mundial Colombia, Bogotá. Disponible en http://gestiondelriesgo.gov.co/sigpad/archivos/GESTIONDELRIESGOWEB.pdf Consultado: 30. Sep. 2020. | |
dc.relation | Banomyong, R., & Julagasigorn, P. (2017). The potential role of philanthropy in humanitarian supply chains delivery: the case of Thailand. Journal of Humanitarian Logistics and Supply Chain Management, 7 (3), 284-303. Doi: https://doi.org/10.1108/JHLSCM-05-2017-0017 | |
dc.relation | Barbarosoğlu, G. & Arda, Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research Society, 55 (1), 43-53. Doi: https://doi.org/10.1057/palgrave.jors.2601652 | |
dc.relation | Basak, B. A., & Gupta, S. (2017). Developing an agent-based model for pilgrim evacuation using visual intelligence: A case study of Ratha Yatra at Puri. Computers Environment and Urban Systems, 64, 118-131. Doi: https://doi.org/10.1016/j.compenvurbsys.2017.01.006 | |
dc.relation | Beamon, B. M., & Balcik, B. (2008). Performance measurement in humanitarian relief chains. International Journal of Public Sector Management, 21 (1), 4-25. Doi: https://doi.org/10.1108/09513550810846087 | |
dc.relation | Besiou, M., Pedraza-Martinez, A. J., & Van Wassenhove, L. N. (2014). Vehicle Supply Chains in Humanitarian Operations: Decentralization, Operational Mix, and Earmarked Funding. Production and Operations Management, 23 (11), 1950-1965. Doi: https://doi.org/10.1111/poms.12215 | |
dc.relation | Besiou, M., Stapleton, O., & Van Wassenhove, L. N. (2011). System dynamics for humanitarian operations. Journal of Humanitarian Logistics and Supply Chain Management, 1 (1), 78-103. Doi: https://doi.org/10.1108/20426741111122420 | |
dc.relation | Bharandev, S., Mukul Ali, S. K., & Sindhu. (2016). Logistics Planning in Natural Disasters. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 23-31. Doi: https://doi.org/10.1007/978-81-322-2416-7_2 | |
dc.relation | BID. (2002). An improbable city. Inter-American Development Bank, Washington. Disponible en https://www.iadb.org/en/news/webstories/2002-03-01/an-improbable-city%2C8310.html. Consultado: 30. Sep. 2020. | |
dc.relation | Blome, C., Tobias, S., & Dominik, E. (2014). The impact of knowledge transfer and complexity on supply chain flexibility: A knowledge-based view. International Journal of Production Economics, 147, 307-316. Doi: https://doi.org/10.1016/j.ijpe.2013.02.028 | |
dc.relation | Bohtan, A., Vrat, P., & Vij, A. K. (2016). Peculiarities of Disaster Management in a High-Altitude Area. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 273-296. Doi: https://doi.org/10.1007/978-81-322-2416-7_19 | |
dc.relation | Borshchev, A., & Filippov, A. (2004). From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools. The 22nd International Conference of the System Dynamics Society. Oxford, Inglaterra, Julio 25-29 2004, pp. 1-23. | |
dc.relation | Brito Jr., I., Rosis, C. H. V., Carneiro, P. V., Leiras, A., & Yoshizaki, H. T. Y. (2014). Proposal of a natural disaster training program by considering the previous victims’ profile. Ambiente & Sociedade, 17 (4), 153-176. Doi: https://doi.org/10.1590/1809-4422ASOC1092V1742014 | |
dc.relation | Burnard, K., & Bhamra, R. (2011). Organisational resilience: development of a conceptual framework for organisational responses. International Journal of Production Research, 49 (18), 5581-5599. Doi: https://doi.org/10.1080/00207543.2011.563827 | |
dc.relation | Campos, A., Mossbrucker, H., & Karremans, J. (2009). La gestión local del riesgo en una ciudad andina: Manizales, un caso integral, ilustrativo y evaluado. Lima, Perú: Editorial Secretaría General de La Comunidad Andina. Disponible en https://repositorio.gestiondelriesgo.gov.co/handle/20.500.11762/19760. Consultado: 2. Oct. 2020. | |
dc.relation | Cardona, O. D. (2006). A System of Indicators for Disaster Risk Management in the Americas. En Birkmann, J. (Ed.), Measuring Vulnerability to Natural Hazards—Towards Disaster Resilient Societies. Tokyo, Nueva York, París: UNUPress. pp. 189-209. | |
dc.relation | Castrillón, O. D., Giraldo, J. A., & Sarache, W. (2009). Técnicas de programación de la producción: aplicación en ambientes job shop. Manizales: Editorial Universidad Nacional de Colombia. | |
dc.relation | Caunhye, A. M., Zhang, Y., Li, M., & Nie, X. (2016). A location-routing model for prepositioning and distributing emergency supplies. Transportation Research Part E: Logistics and Transportation Review, 90, 161-176. Doi: https://doi.org/10.1016/j.tre.2015.10.011 | |
dc.relation | Cepeda-Susatama, K. D., Durango-Ruiz, K. A., & Bohórquez-Arévalo, L. E. (2017). Modelación y simulación en agentes como alternativa para el estudio de las organizaciones empresariales. Ingeniería Solidaria, 13 (22), 103-119. Doi: https://doi.org/10.16925/in.v13i22.1838 | |
dc.relation | Chakravarty, A. K. (2014). Humanitarian relief chain: Rapid response under uncertainty. International Journal of Production Economics, 151 (1), 146-157. Doi: https://doi.org/10.1016/j.ijpe.2013.10.007 | |
dc.relation | Chan, H. K., & Chan, F. T. S. (2010). A review of coordination studies in the context of supply chain dynamics. International Journal of Production Research, 48 (10), 2793-2819. Doi: https://doi.org/10.1080/00207540902791843 | |
dc.relation | Charbonneau, D., Dornhaus, A. (2015). When doing nothing is something. How task allocation strategies compromise between flexibility, efficiency, and inactive agents. Journal of Bioeconomics, 17, 217-242. Doi: https://doi.org/10.1007/s10818-015-9205-4 | |
dc.relation | Charles, A. (2010). Improving the design and management of agile supply chains: feedback and application in the context of humanitarian aid. Tesis Doctoral. Université de Toulouse, Toulouse (Francia). | |
dc.relation | Charles, A., & Lauras, M. (2011). An enterprise modelling approach for better optimisation modelling: application to the humanitarian relief chain coordination problem. OR Spectrum, 33 (3), 815-841. Doi: https://doi.org/10.1007/s00291-011-0255-2 | |
dc.relation | Charles, A., Lauras, M., Van Wassenhove, L. N., & Dupont, L. (2016). Designing an efficient humanitarian supply network. Journal of Operations Management, 47-48, 58-70. Doi: https://doi.org/10.1016/j.jom.2016.05.012 | |
dc.relation | Chong, M., Lazo, J. G., Pereda, M. C., & Machuca, J. M. (2019). Goal programming optimization model under uncertainty and the critical areas characterization in humanitarian logistics management. Journal of Humanitarian Logistics and Supply Chain Management, 9 (1), 82-107. Doi: https://doi.org/10.1108/JHLSCM-04-2018-0027 | |
dc.relation | Collins, A. J., & Frydenlund, E. (2016). Agent-based modeling and strategic group formation: a refugee case study. En Proceedings of the 2016 Winter Simulation Conference. Arlington, USA, 11-14 Diciembre 2016, pp. 1289-1300. Doi: https://doi.org/10.1109/WSC.2016.7822184 | |
dc.relation | Connelly, E. B., Lambert, J. H., & Thekdi, S. A. (2016). Robust Investments in Humanitarian Logistics and Supply Chains for Disaster Resilience and Sustainable Communities. Natural Hazards Review, 17 (1), Número de artículo: 04015017, 11 páginas. Doi: https://doi.org/10.1061/(ASCE)NH.1527-6996.0000187 | |
dc.relation | Córdova, C. A. (2007). Consideraciones sobre metodología de la investigación. Centro de Estudios sobre Cultura e Identidad, Universidad de Holguín “Oscar Lucero Moya”, Holguín, Cuba. Disponible en https://studylib.es/doc/3172532/consideraciones-sobre-metodologia-de-la-investigacion. Consultado: 16. Oct. 2018. | |
dc.relation | Corpocaldas. (2013). Plan de ordenación y manejo ambiental de la cuenca hidrográfica del río Chinchiná en el departamento de Caldas – POMCA Chinchiná. Corporación Autónoma Regional de Caldas, Manizales. Disponible en http://www.corpocaldas.gov.co/publicaciones/1508/1-SintesisPOMCARioChinchina_.pdf. Consultado: 9. Abr. 2017. | |
dc.relation | Cotes, N., & Cantillo, V. (2019). Including deprivation costs in facility location models for humanitarian relief logistics. Socio-Economic Planning Sciences, 65, 89-100. Doi: https://doi.org/10.1016/j.seps.2018.03.002 | |
dc.relation | Cozzolino, A. (2012). Humanitarian Logistics: Cross-Sector Cooperation in Disaster Relief Management. Nueva York: Springer. | |
dc.relation | Cozzolino, A., Wankowicz, E., & Massaroni, E. (2017). Logistics service providers' engagement in disaster relief initiatives: An exploratory analysis. International Journal of Quality and Service Sciences, 9 (3-4), 269-291. Doi: https://doi.org/10.1108/IJQSS-04-2017-0040 | |
dc.relation | Crooks, A. T., & Wise, S. (2013). GIS and agent-based models for humanitarian assistance. Computers Environment and Urban Systems, 41, 100-111. Doi: https://doi.org/10.1016/j.compenvurbsys.2013.05.003 | |
dc.relation | Cruz, M., & Martínez, M. C. (2012). Perfeccionamiento de un instrumento para la selección de expertos en las investigaciones educativas. Revista Electrónica de Investigación Educativa, 14 (2), 167–179. | |
dc.relation | Cruz-Castro, O., Vertiz-Camaron, G., & Apolonio-Oro, S. (2019). Third and fourth-party logistics providers groups formation focused on humanitarian logistics in the face of coastal flooding. International Journal of Combinatorial Optimization Problems and Informatics, 10 (1), 32-40. | |
dc.relation | Dalkey, N. (1969). The Delphi method: An experimental study of group opinion. Futures, 1 (5), 408-426. Doi: http://doi.org/10.1016/S0016-3287(69)80025-X | |
dc.relation | DANE. (2020). Colombia – Censo Nacional de Población y Vivienda – CNPV – 2018. Departamento Administrativo Nacional de Estadística, Bogotá. Disponible en https://sitios.dane.gov.co/cnpv/#!/. Consultado: 30. Oct. 2020. | |
dc.relation | Das, R. (2018). Disaster preparedness for better response: Logistics perspectives. International Journal of Disaster Risk Reduction, 31, 153-159. Doi: https://doi.org/10.1016/j.ijdrr.2018.05.005 | |
dc.relation | Das, R., & Hanaoka, S. (2014). An agent-based model for resource allocation during relief distribution. Journal of Humanitarian Logistics and Supply Chain Management, 4 (2), 265-285. Doi: https://doi.org/10.1108/JHLSCM-07-2013-0023 | |
dc.relation | Davis, L. B., Samanlioglu, F., Qu, X., & Root, S. (2013). Inventory planning and coordination in disaster relief efforts. International Journal of Production Economics, 141 (2), 561-573. Doi: https://doi.org/10.1016/j.ijpe.2012.09.012 | |
dc.relation | Day, J. M. (2014). Fostering emergent resilience: the complex adaptive supply network of disaster relief. International Journal of Production Research, 52 (7), 1970-1988. Doi: https://doi.org/10.1080/00207543.2013.787496 | |
dc.relation | Day, J. M., Melnyk, S. A., Larson, P. D., Davis, E. W., & Whybark, D. C. (2012). Humanitarian and disaster relief supply chains: a matter of life and death. Journal of Supply Chain Management, 48 (2), 21-36. Doi: https://doi.org/10.1111/j.1745-493X.2012.03267.x | |
dc.relation | De Leeuw, S., Vis, I. F. A., & Jonkman, S. N. (2012). Exploring Logistics Aspects of Flood Emergency Measures. Journal of Contingencies and Crisis Management, 20 (3), 166-179. Doi: https://doi.org/10.1111/j.1468-5973.2012.00667.x | |
dc.relation | Díaz, A., & Olaya, C. (2017). An Engineering View for Social Systems: Agency as an Operational Principle for Designing Higher Education Access Policies. Systemic Practice and Action Research, 30 (6), 627-649. Doi: https://doi.org/10.1007/s11213-017-9412-0 | |
dc.relation | Diaz, R., Kumar, S., & Behr, J. (2015). Housing recovery in the aftermath of a catastrophe: Material resources perspective. Computers & Industrial Engineering, 81, 130-139. Doi: https://doi.org/10.1016/j.cie.2014.12.036 | |
dc.relation | Diedrichs, D. R., Phelps, K., & Isihara, P. A. (2016). Quantifying communication effects in disaster response logistics: A multiple network system dynamics model. Journal of Humanitarian Logistics and Supply Chain Management, 6 (1), 24-45. Doi: https://doi.org/10.1108/JHLSCM-09-2014-0031 | |
dc.relation | Domínguez-Machuca, J. A., García, G. S., Domínguez-Machuca, M. A., Ruiz, J. A., & Álvarez, G. M. J. (1995). Dirección de Operaciones: Aspectos estratégicos en la producción y los servicios. Madrid: McGraw-Hill. | |
dc.relation | Drakaki, M., Gören, H. G., & Tzionas, P. (2018). An intelligent multi-agent based decision support system for refugee settlement siting. International Journal of Disaster Risk Reduction, 31, 576-588. Doi: https://doi.org/10.1016/j.ijdrr.2018.06.013 | |
dc.relation | Dubey, R., & Gunasekaran, A. (2015). The sustainable humanitarian supply chain design: agility, adaptability and alignment. International Journal of Logistics: Research and Applications, 19 (1), 62-82. Doi: https://doi.org/10.1080/13675567.2015.1015511 | |
dc.relation | Eco, U. (2001). Cómo se hace una tesis: Técnicas y procedimientos de estudio, investigación y escritura. Barcelona: Gedisa Editorial. | |
dc.relation | Eftekhar, M., Li, H. M., Van Wassenhove, L. N., & Webster, S. (2017). The Role of Media Exposure on Coordination in the Humanitarian Setting. Production and Operations Management, 26 (5), 802-816. Doi: https://doi.org/10.1111/poms.12669 | |
dc.relation | Eftekhar, M., Masini, A., Robotis, A., & Van Wassenhove, L. N. (2014). Vehicle Procurement Policy for Humanitarian Development Programs. Production and Operations Management, 23 (6), 951-964. Doi: https://doi.org/10.1111/poms.12108 | |
dc.relation | EM-DAT: Centre for Research on the Epidemiology of Disasters. (2018). The OFDA/CRED International Disaster Database. Université Catholique de Louvain, Bruselas, Bélgica. Disponible en http://www.emdat.be/. Consultado: 19. Dic. 2018. | |
dc.relation | Ergun, Ö., Gui, L., Stamm, J. L. H., Keskinocak, P., & Swann, J. (2014). Improving Humanitarian Operations through Technology-Enabled Collaboration. Production and Operations Management, 23 (6), 1002-1014. Doi: https://doi.org/10.1111/poms.12107 | |
dc.relation | FEMA. (2010). The Four Phases Of Emergency Management. Federal Emergency Management Agency, Washington. Disponible en https://training.fema.gov/emiweb/downloads/is10_unit3.doc. Consultado: 26. Feb. 2016. | |
dc.relation | Fernando, R. L. S., & Muthulingam, A. (2015). Effectiveness of Administrative Preparedness: A Case Study on Flooding Conditions in Ambagamuwa Korale Division of Nuwara Eliya District in Sri Lanka. En Ha, H., Fernando, R. L. S., & Mahmood, A. (Eds.), Strategic Disaster Risk Management in Asia. Nueva Delhi: Springer. pp. 87-98. Doi: https://doi.org/10.1007/978-81-322-2373-3_7 | |
dc.relation | Ferrer, J. M., Ortuño, M. T., & Tirado, G. (2015). A GRASP metaheuristic for humanitarian aid distribution. Journal of Heuristics, 22 (1), 55-87. Doi: https://doi.org/10.1007/s10732-015-9302-5 | |
dc.relation | Fikar, C., Gronalt, M., & Hirsch, P. (2016). A decision support system for coordinated disaster relief distribution. Expert Systems with Applications, 57, 104-116. Doi: https://doi.org/10.1016/j.eswa.2016.03.039 | |
dc.relation | Fikar, C., Hirsch, P., & Nolz, P. C. (2018). Agent-based simulation optimization for dynamic disaster relief distribution. Central European Journal of Operations Research, 26 (2), 423-442. Doi: https://doi.org/10.1007/s10100-017-0518-3 | |
dc.relation | Fontainha, T. C., Leiras, A., Bandeira, R. A. D., Scavarda, L. F. (2017). Public-Private-People Relationship Stakeholder Model for disaster and humanitarian operations. International Journal of Disaster Risk Reduction, 22, 371-386. Doi: https://doi.org/10.1016/j.ijdrr.2017.02.004 | |
dc.relation | Galán, J. M. (2007). Evaluación integradora de políticas de agua: modelado y simulación con sociedades artificiales de agentes. Tesis Doctoral. Universidad de Burgos, Burgos (España). | |
dc.relation | Galindo, G., & Batta, R. (2013). Review of recent developments in OR/MS research in disaster operations management. European Journal of Operational Research, 230 (2), 201-211. Doi: https://doi.org/10.1016/j.ejor.2013.01.039 | |
dc.relation | Ganguly, K. K., & Rai, S. S. (2016). Managing the humanitarian relief chain: the Uttarakhand disaster issues. Journal of Advances in Management Research, 13 (1), 92-111. Doi: https://doi.org/10.1108/JAMR-09-2014-0052 | |
dc.relation | Ganguly, K. K., Padhy, R. K., & Rai, S. S. (2017). Managing the humanitarian supply chain: a fuzzy logic approach. International Journal of Disaster Resilience in the Built Environment, 8 (5), 521-536. Doi: https://doi.org/10.1108/IJDRBE-07-2015-0038 | |
dc.relation | García, J. (2011). The Moral Herd: Groups and the Evolution of Altruism and Cooperation. Tesis Doctoral. Vrije Universiteit Amsterdam, Amsterdam (Países Bajos). | |
dc.relation | García, J., & Van Veelen, M. (2018). No Strategy Can Win in the Repeated Prisoner's Dilemma: Linking Game Theory and Computer Simulations. Frontiers in Robotics and AI, 5, Número de artículo: 102, 14 páginas. Doi: https://doi.org/10.3389/frobt.2018.00102 | |
dc.relation | Garrido, R. A., Lamas, P., & Pino, F. J. (2015). A stochastic programming approach for floods emergency logistics. Transportation Research Part E: Logistics and Transportation Review, 75, 18-31. Doi: https://doi.org/10.1016/j.tre.2014.12.002 | |
dc.relation | Gavidia, J. V. (2017). A model for enterprise resource planning in emergency humanitarian logistics. Journal of Humanitarian Logistics and Supply Chain Management, 7 (3), 246-265. Doi: https://doi.org/10.1108/JHLSCM-02-2017-0004 | |
dc.relation | Giachetti, R. E., Martinez, L. D., Saenz, O. A., & Chen, C. S. (2003). Analysis of the Structural Measures of Flexibility and Agility Using a Measurement Theoretical Framework. International Journal of Production Economics, 86 (1), 47-62. Doi: https://doi.org/10.1016/S0925-5273(03)00004-5 | |
dc.relation | Gibbons, D. E., & Samaddar, S. (2009). Designing Referral Network Structures and Decision Rules to Streamline Provision of Urgent Health and Human Services. Decision Sciences, 40 (2), 351-371. Doi: https://doi.org/10.1111/j.1540-5915.2009.00230.x | |
dc.relation | Goldman, S. L. (2017). Compromised Exactness and the Rationality of Engineering. En García‐Díaz, C., & Olaya, C. (Eds.), Social Systems Engineering: The Design of Complexity. New York: John Wiley & Sons. pp. 11-30. Doi: https://doi.org/10.1002/9781118974414.ch1 | |
dc.relation | Golicic, S. L., Davis, D. F., & McCarthy, T. M. (2005). A Balanced Approach to Research in Supply Chain Management. En Kotzab, H., Seuring, S., Müller, M., & Reiner, G. (Eds.), Research Methodologies in Supply Chain Management. Heidelberg: Physica-Verlag. pp.15-29. Doi: https://doi.org/10.1007/3-7908-1636-1_2 | |
dc.relation | Gómez-Ramírez, D. M. (2017). Evaluación de las capacidades de logística humanitaria para la atención de desastres naturales en la red de ayuda humanitaria. El caso de Manizales. Tesis de Maestría. Universidad Nacional de Colombia, Manizales (Colombia). | |
dc.relation | Gösling, H., & Geldermann, J. (2014). A Framework to Compare OR Models for Humanitarian Logistics. Procedia Engineering, 78, 22-28. Doi: https://doi.org/10.1016/j.proeng.2014.07.034 | |
dc.relation | Granberg, T. A. (2013). Preparedness Measures for Emergency and Disaster Response. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 59-75. Doi: https://doi.org/10.1007/978-1-4614-7007-6_4 | |
dc.relation | Guerrero, W. J. (2013). Models and Optimization Methods for the Inventory-Location-Routing Problem. Tesis Doctoral. Universidad de los Andes, Bogotá (Colombia). | |
dc.relation | Guo, X. S., & Kapucu, N. (2020). Engaging Stakeholders for Collaborative Decision Making in Humanitarian Logistics Using System Dynamics. Journal of Homeland Security And Emergency Management, 17 (1), Número de artículo: 20180061, 13 páginas. Doi: https://doi.org/10.1515/jhsem-2018-0061 | |
dc.relation | Gutjahr, W. J., & Dzubur, N. (2016). Bi-objective bilevel optimization of distribution center locations considering user equilibria. Transportation Research Part E: Logistics and Transportation Review, 85, 1-22. Doi: https://doi.org/10.1016/j.tre.2015.11.001 | |
dc.relation | Gutjahr, W. J., & Nolz, P. C. (2016). Multicriteria optimization in humanitarian aid. European Journal of Operational Research, 252 (2), 351-366. Doi: https://doi.org/10.1016/j.ejor.2015.12.035 | |
dc.relation | Haavisto, I., & Goentzel, J. (2015). Measuring humanitarian supply chain performance in a multi-goal context. Journal of Humanitarian Logistics and Supply Chain Management, 5 (3), 300-324. Doi: https://doi.org/10.1108/JHLSCM-07-2015-0028 | |
dc.relation | Habib, M. S., Lee, Y. H., & Memon, M. S. (2016). Mathematical Models in Humanitarian Supply Chain Management: A Systematic Literature Review. Mathematical Problems in Engineering, 2016, Número de artículo: 3212095, 20 páginas. Doi: https://doi.org/10.1155/2016/3212095 | |
dc.relation | Hadiguna, R. A., Kamil, I., Delati, A., & Reed, R. (2014). Implementing a web-based decision support system for disaster logistics: A case study of an evacuation location assessment for Indonesia. International Journal of Disaster Risk Reduction, 9, 38-47. Doi: https://doi.org/10.1016/j.ijdrr.2014.02.004 | |
dc.relation | Haghani, A., & Oh, S. C. (1996). Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transportation Research Part A: Policy and Practice, 30 (3), 231-250. Doi: https://doi.org/10.1016/0965-8564(95)00020-8 | |
dc.relation | Haghi, M., Ghomi, S. M. T. F., & Jolai, F. (2017). Developing a robust multi-objective model for pre/post disaster times under uncertainty in demand and resource. Journal of Cleaner Production, 154, 188-202. Doi: https://doi.org/10.1016/j.jclepro.2017.03.102 | |
dc.relation | Hammond, R. A. (2015). Considerations and Best Practices in Agent-Based Modeling to Inform Policy. En Wallace, R., Geller, A., & Ogawa, V. A. (Eds.), Assessing the Use of Agent-Based Models for Tobacco Regulation. Washington, D.C.: The National Academies Press. pp. 161-193. | |
dc.relation | Hardoy, J., & Velásquez, L. S. (2014). Re-thinking "Biomanizales": addressing climate change adaptation in Manizales, Colombia. Environment and Urbanization, 26 (1), 53-68. Doi: https://doi.org/10.1177/0956247813518687 | |
dc.relation | Hasanzadeh, H., & Bashiri, M. (2016). An efficient network for disaster management: Model and solution. Applied Mathematical Modelling, 40 (5-6), 3688-3702. Doi: https://doi.org/10.1016/j.apm.2015.09.113 | |
dc.relation | Hashemipour, M., Stuban, S., & Dever, J. (2018). A disaster multiagent coordination simulation system to evaluate the design of a first-response team. Systems Engineering, 21 (4), 322-344. Doi: https://doi.org/10.1002/sys.21437 | |
dc.relation | Hawe, G. I., Coates, G., Wilson, D. T., & Crouch, R. S. (2015). Agent-based simulation of emergency response to plan the allocation of resources for a hypothetical two-site major incident. Engineering Applications of Artificial Intelligence, 46, 336-345. Doi: https://doi.org/10.1016/j.engappai.2015.06.023 | |
dc.relation | He, F., & Zhuang, J. (2016). Balancing pre-disaster preparedness and post-disaster relief. European Journal of Operational Research, 252 (1), 246-256. Doi: https://doi.org/10.1016/j.ejor.2015.12.048 | |
dc.relation | Heaslip, G., Kovács, G., & Grant, D. B. (2018). Servitization as a competitive difference in humanitarian logistics. Journal of Humanitarian Logistics and Supply Chain Management, 8 (4), 497-517. Doi: https://doi.org/10.1108/JHLSCM-08-2017-0042 | |
dc.relation | Heaslip, G., Sharif, A. M., & Althonayan, A. (2012). Employing a systems-based perspective to the identification of inter-relationships within humanitarian logistics. International Journal of Production Economics, 139 (2), 377-392. Doi: https://doi.org/10.1016/j.ijpe.2012.05.022 | |
dc.relation | Hellingrath, B., Babun, T. A., Smith, J. F., & Link, D. (2015). Disaster Management Capacity Building at Airports and Seaports. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 87-112. Doi: https://doi.org/10.1007/978-3-319-15455-8_6 | |
dc.relation | Herlin, H., & Pazirandeh, A. (2015). Avoiding the pitfalls of cooperative purchasing through control and coordination: Insights from a humanitarian context. International Journal of Procurement Management, 8 (3), 303-325. Doi: https://doi.org/10.1504/IJPM.2015.069155 | |
dc.relation | Hernández-Sampieri, R., Fernández-Collado, C., & Baptista-Lucio, P. (2014). Metodología de la investigación. 6a. ed. México D.F.: McGraw-Hill. | |
dc.relation | Holguín-Veras, J., Jaller, M., Van Wassenhove, L. N., Pérez, N., & Wachtendorf, T. (2012). On the unique features of post-disaster humanitarian logistics. Journal of Operations Management, 30 (7-8), 494-506. Doi: https://doi.org/10.1016/j.jom.2012.08.003 | |
dc.relation | Holguín-Veras, J., Pérez, N., Jaller, M., Van Wassenhove, L. N., & Aros-Vera, F. (2013). On the appropriate objective function for post-disaster humanitarian logistics models. Journal of Operations Management, 31 (5), 262-280. Doi: https://doi.org/10.1016/j.jom.2013.06.002 | |
dc.relation | Holguín-Veras, J., Taniguchi, E., Jaller, M., Aros-Vera, F., Ferreira, F., & Thompson, R. G. (2014). The Tohoku disasters: Chief lessons concerning the post disaster humanitarian logistics response and policy implications. Transportation Research Part A: Policy and Practice, 69, 86-104. Doi: https://doi.org/10.1016/j.tra.2014.08.003 | |
dc.relation | Hong, X., Lejeune, M. A., & Noyan, N. (2015). Stochastic Network Design for Disaster Preparedness. IIE Transactions, 47 (4), 329-357. Doi: https://doi.org/10.1080/0740817X.2014.919044 | |
dc.relation | Hooshangi, N., & Alesheikh, A. A. (2018). Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents. ISPRS International Journal of Geo-Information, 7 (1), Número de artículo: 27, 22 páginas. Doi: https://doi.org/10.3390/ijgi7010027 | |
dc.relation | Hoyos, M. C., Morales, R. S., & Akhavan-Tabatabaei, R. (2015). OR models with stochastic components in disaster operations management: A literature survey. Computers & Industrial Engineering, 82, 183-197. Doi: https://doi.org/10.1016/j.cie.2014.11.025 | |
dc.relation | Hu, S. L., & Dong, Z. S. (2019). Supplier selection and pre-positioning strategy in humanitarian relief. Omega-International Journal of Management Science, 83, 287-298. Doi: https://doi.org/10.1016/j.omega.2018.10.011 | |
dc.relation | IFRC. (2012). The disaster relief emergency fund. International Federation of Red Cross and Red Crescent Societies, Ginebra. Disponible en http://www.ifrc.org/dref. Consultado: 28. Dic. 2018. | |
dc.relation | IGAC. (2012). Mapa Oficial Físico-político de Colombia. Instituto Geográfico Agustín Codazzi, Bogotá. Disponible en https://geoportal.igac.gov.co/contenido/mapas-nacionales. Consultado: 1. Oct. 2020. | |
dc.relation | IPCC. (2012). Managing the risks of extreme events and disasters to advance climate change adaptation - Summary for policymakers. The Intergovernmental Panel on Climate Change, Ginebra. Disponible en https://www.ipcc.ch/site/assets/uploads/2018/03/SREX_FD_SPM_final-2.pdf. Consultado: 20. Dic. 2018. | |
dc.relation | Iqbal, S., Sardar, M. U., Lodhi, F. K., & Hasan, O. (2018). Statistical model checking of relief supply location and distribution in natural disaster management. International Journal of Disaster Risk Reduction, 31, 1043-1053. Doi: https://doi.org/10.1016/j.ijdrr.2018.04.010 | |
dc.relation | Izquierdo, L. R., Galán, J. M., Santos, J. I., & Del Olmo, R. (2008). Modelado de sistemas complejos mediante simulación basada en agentes y mediante dinámica de sistemas. Empiria. Revista de metodología de ciencias sociales, 16, 85-112. Doi: https://doi.org/10.5944/empiria.16.2008.1391 | |
dc.relation | Jahre, M. (2017). Humanitarian supply chain strategies – a review of how actors mitigate supply chain risks. Journal of Humanitarian Logistics and Supply Chain Management, 7 (2), 82-101. Doi: https://doi.org/10.1108/JHLSCM-12-2016-0043 | |
dc.relation | Jahre, M., & Jensen, L. M. (2010). Coordination in humanitarian logistics through clusters. International Journal of Physical Distribution & Logistics Management, 40 (8-9), 657-674. Doi: https://doi.org/10.1108/09600031011079319 | |
dc.relation | Jahre, M., Ergun, O., & Goentzel, J. (2015). One Size Fits All? Using Standard Global Tools in Humanitarian Logistics. Procedia Engineering, 107, 18-26. Doi: https://doi.org/10.1016/j.proeng.2015.06.054 | |
dc.relation | Jahre, M., Pazirandeh, A., & Van Wassenhove, L. N. (2016). Defining logistics preparedness: a framework and research agenda. Journal of Humanitarian Logistics and Supply Chain Management, 6 (3), 372-398. Doi: https://doi.org/10.1108/JHLSCM-04-2016-0012 | |
dc.relation | Jensen, L. M., & Hertz, S. (2016). The coordination roles of relief organisations in humanitarian logistics. International Journal of Logistics Research and Applications, 19 (5), 465-485. Doi: https://doi.org/10.1080/13675567.2015.1124845 | |
dc.relation | John, L., & Ramesh, A. (2016). Modeling the barriers of humanitarian supply chain management in India. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 61-82. Doi: https://doi.org/10.1007/978-81-322-2416-7_5 | |
dc.relation | Kabra, G., & Ramesh, A. (2015). Segmenting critical factors for enhancing the use of IT in humanitarian supply chain management. Procedia - Social and Behavioral Sciences, 189, 144-152. Doi: https://doi.org/10.1016/j.sbspro.2015.03.208 | |
dc.relation | Kabra, G., Ramesh, A., & Arshinder, K. (2015). Identification and prioritization of coordination barriers in humanitarian supply chain management. International Journal of Disaster Risk Reduction, 13, 128-138. Doi: https://doi.org/10.1016/j.ijdrr.2015.01.011 | |
dc.relation | Kabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioural intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34 (7), 1250-1261. Doi: https://doi.org/10.1016/j.tele.2017.05.010 | |
dc.relation | Kaneberg, E. (2017). Managing military involvement in emergency preparedness in developed countries. Journal of Humanitarian Logistics and Supply Chain Management, 7 (3), 350-374. Doi: https://doi.org/10.1108/JHLSCM-04-2017-0014 | |
dc.relation | Kimms, A., & Maiwald, M. (2018). Bi-objective safe and resilient urban evacuation planning. European Journal of Operational Research, 269 (3), 1122-1136. Doi: https://doi.org/10.1016/j.ejor.2018.02.050 | |
dc.relation | Kleijnen, J. P. C. (1995). Verification and validation of simulation models. European Journal of Operational Research, 82 (1), 145-162. Doi: https://doi.org/10.1016/0377-2217(94)00016-6 | |
dc.relation | Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (2015). Sustainability in Humanitarian Logistics - Why and How? En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 3-9. Doi: https://doi.org/10.1007/978-3-319-15455-8_1 | |
dc.relation | Kovács, G., & Moshtari, M. (2019). A roadmap for higher research quality in humanitarian operations: A methodological perspective. European Journal of Operational Research, 276 (2), 395-408. Doi: https://doi.org/10.1016/j.ejor.2018.07.052 | |
dc.relation | Kovács, G., & Spens, K. M. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution & Logistics Management, 37 (2), 99-114. Doi: https://doi.org/10.1108/09600030710734820 | |
dc.relation | Kovács, G., & Spens, K. M. (2009). Identifying challenges in humanitarian logistics. International Journal of Physical Distribution & Logistics Management, 39 (6), 506-528. Doi: https://doi.org/10.1108/09600030910985848 | |
dc.relation | Kovács, G., & Tatham, P. (2009). Responding to disruptions in the supply network - From dormant to action. Journal of Business Logistics, 30 (2), 215-229. Doi: https://doi.org/10.1002/j.2158-1592.2009.tb00121.x | |
dc.relation | Krejci, C. C. (2015). Hybrid simulation modeling for humanitarian relief chain coordination. Journal of Humanitarian Logistics and Supply Chain Management, 5 (3), 325-347. Doi: https://doi.org/10.1108/JHLSCM-07-2015-0033 | |
dc.relation | Krick, E. V. (1979). Fundamentos de ingeniería: métodos, conceptos y resultados. 1a. ed. México D.F.: Editorial Limusa. | |
dc.relation | Krishnamurthy, A., Roy, D., & Bhat, S. (2013). Analytical Models for Estimating Waiting Times at a Disaster Relief Center. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 21-41. Doi: https://doi.org/10.1007/978-1-4614-7007-6_2 | |
dc.relation | Kumar, R. (2011). Research methodology: A step-by-step guide for beginners. 3a. ed. Londres: SAGE Publications Ltd. | |
dc.relation | Kumar, S., & Havey, T. (2013). Before and after disaster strikes: A relief supply chain decision support framework. International Journal of Production Economics, 145 (2), 613-629. Doi: https://doi.org/10.1016/j.ijpe.2013.05.016 | |
dc.relation | Kunz, N., & Gold, S. (2015). Sustainable humanitarian supply chain management – exploring new theory. International Journal of Logistics Research and Applications, 20 (2), 85-104. Doi: https://doi.org/10.1080/13675567.2015.1103845 | |
dc.relation | Kunz, N., Reiner, G., & Gold, S. (2014). Investing in disaster management capabilities versus pre-positioning inventory: A new approach to disaster preparedness. International Journal of Production Economics, 157, 261-272. Doi: https://doi.org/10.1016/j.ijpe.2013.11.002 | |
dc.relation | Kusumastuti, R. D., Wibowo, S. S., & Insanita, R. (2013). Modeling Facility Locations for Relief Logistics in Indonesia. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 183-205. Doi: https://doi.org/10.1007/978-1-4614-7007-6_10 | |
dc.relation | Labarthe, O., Espinasse, B., Ferrarini, A., & Montreuil, B. (2007). Toward a methodological framework for agent-based modelling and simulation of supply chains in a mass customization context. Simulation Modelling Practice and Theory, 15 (2), 113-136. Doi: https://doi.org/10.1016/j.simpat.2006.09.014 | |
dc.relation | Landeta, J., Barrutia, J., & Lertxundi, A. (2011). Hybrid Delphi: A methodology to facilitate contribution from experts in professional contexts. Technological Forecasting & Social Change, 78 (9), 1629-1641. Doi: https://doi.org/10.1016/j.techfore.2011.03.009 | |
dc.relation | Langellier, B. A., Bilal, U., Montes, F., Meisel, J. D., Cardoso, L. O., & Hammond, R. (2019). Complex Systems Approaches to Diet: A Systematic Review. American Journal of Preventive Medicine, 57 (2), 273-281. Doi: https://doi.org/10.1016/j.amepre.2019.03.017 | |
dc.relation | Larson, P. D., & Foropon, C. (2018). Process improvement in humanitarian operations: an organisational theory perspective. International Journal of Production Research, 56 (21), 6828-6841. Doi: https://doi.org/10.1080/00207543.2018.1424374 | |
dc.relation | Liberatore, F., Ortuño, M. T., Tirado, G., Vitoriano, B., & Scaparra, M. P. (2014). A hierarchical compromise model for the joint optimization of recovery operations and distribution of emergency goods in Humanitarian Logistics. Computers & Operations Research, 42, 3-13. Doi: https://doi.org/10.1016/j.cor.2012.03.019 | |
dc.relation | Liu, Y., & Guo, B. (2014). A Lexicographic Approach to Postdisaster Relief Logistics Planning Considering Fill Rates and Costs under Uncertainty. Mathematical Problems in Engineering, 2014, Número de artículo: 939853, 17 páginas. Doi: https://doi.org/10.1155/2014/939853 | |
dc.relation | Lorca, Á., Çelik, M., Ergun, Ö., & Keskinocak, P. (2015). A decision-support tool for post-disaster debris operations. Procedia Engineering, 107, 154-167. Doi: https://doi.org/10.1016/j.proeng.2015.06.069 | |
dc.relation | Lu, Q., Goh, M., & de Souza, R. (2018). An empirical investigation of swift trust in humanitarian logistics operations. Journal of Humanitarian Logistics and Supply Chain Management, 8 (1), 70-86. Doi: https://doi.org/10.1108/JHLSCM-07-2017-0033 | |
dc.relation | Macal, C. M., & North, M. J. (2010). Tutorial on agent-based modelling and simulation. Journal of Simulation, 4 (3), 151-162. Doi: https://doi.org/10.1057/jos.2010.3 | |
dc.relation | Macal, C. M., & North, M. J. (2014). Introductory Tutorial: Agent-Based Modeling and Simulation. En Proceedings of the 2014 Winter Simulation Conference. Savannah, USA, 7-10 Diciembre 2014, pp. 6-20. Doi: https://doi.org/10.1109/WSC.2014.7019874 | |
dc.relation | Maghsoudi, A., & Pazirandeh, A. (2016). Visibility, resource sharing and performance in supply chain relationships: insights from humanitarian practitioners. Supply Chain Management: An International Journal, 21 (1), 125-139. Doi: https://doi.org/10.1108/SCM-03-2015-0102 | |
dc.relation | Manopiniwes, W., & Irohara, T. (2017). Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response. International Journal of Production Research, 55 (4), 979-996. Doi: https://doi.org/10.1080/00207543.2016.1211340 | |
dc.relation | Marcelin, J. M., Horner, M. W., Ozguven, E. E., & Kocatepe, A. (2016). 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, 15, 61-72. Doi: https://doi.org/10.1016/j.ijdrr.2015.12.006 | |
dc.relation | Marcinkowski, J.M. (2017). Japanese and American Approach to Humanitarian Logistics in Natural Disasters' Prevention. Logforum, 13 (2), 171-182. Doi: https://doi.org/10.17270/J.LOG.2017.2.5 | |
dc.relation | Mejia-Argueta, C., Gaytán, J., Caballero, R., Molina, J., & Vitoriano, B. (2018). Multicriteria optimization approach to deploy humanitarian logistic operations integrally during floods. International Transactions in Operational Research, 25 (3), 1053-1079. Doi: https://doi.org/10.1111/itor.12508 | |
dc.relation | Mendenhall, W., & Reinmuth, J. (1981). Estadística para la administración y economía. 3a. ed. México D.F.: Grupo Editorial Iberoamérica. | |
dc.relation | Mendenhall, W., Beaver, R. J., & Beaver, B. M. (2010). Introducción a la probabilidad y estadística. 13a. ed. México D.F.: Cengage Learning Editores. | |
dc.relation | Menth, M. (2014). An Agent-Based Modeling Approach To Assess Coordination Among Humanitarian Relief Providers. Tesis de Maestría. Kansas State University, Manhattan (Estados Unidos). | |
dc.relation | Meredith, J. (1993). Theory Building through Conceptual Methods. International Journal of Operations & Production Management, 13 (5), 3-11. Doi: https://doi.org/10.1108/01443579310028120 | |
dc.relation | Mohan, S., Gopalakrishnan, M., & Mizzi, P. J. (2013). Improving the efficiency of a non-profit supply chain for the food insecure. International Journal of Production Economics, 143 (2), 248-255. Doi: https://doi.org/10.1016/j.ijpe.2011.05.019 | |
dc.relation | Mora-Ochomogo, E. I., Mora-Vargas, J., & Serrato, M. (2016). A Qualitative Analysis of Inventory Management Strategies in Humanitarian Logistics Operations. International Journal of Combinatorial Optimization Problems and Informatics, 7 (1), 40-53. Disponible en http://www.redalyc.org/articulo.oa?id=265245553006. Consultado: 18. Jul. 2016. | |
dc.relation | Moreno, A., Alem, D., & Ferreira, D. (2016). Heuristic approaches for the multiperiod location-transportation problem with reuse of vehicles in emergency logistics. Computers & Operations Research, 69, 79-96. Doi: https://doi.org/10.1016/j.cor.2015.12.002 | |
dc.relation | Moshtari, M. (2016). Inter-Organizational Fit, Relationship Management Capability, and Collaborative Performance within a Humanitarian Setting. Production and Operations Management, 25 (9), 1542-1557. Doi: https://doi.org/10.1111/poms.12568 | |
dc.relation | Moshtari, M., & Gonçalves, P. (2017). Factors Influencing Interorganizational Collaboration within a Disaster Relief Context. Voluntas, 28 (4), 1673-1694. Doi: https://doi.org/10.1007/s11266-016-9767-3 | |
dc.relation | Muggy, L., & Stamm, J. L. H. (2017). Dynamic, robust models to quantify the impact of decentralization in post-disaster health care facility location decisions. Operations Research for Health Care, 12, 43-59. Doi: https://doi.org/10.1016/j.orhc.2017.01.002 | |
dc.relation | Muskat, M., Blackman, D., & Muskat, B. (2012). Mixed methods: Combining expert interviews, cross-impact analysis and scenario development. Electronic Journal of Business Research Methods, 10 (1), 9-21. | |
dc.relation | Nadi, A., & Edrisi, A. (2017). Adaptive multi-agent relief assessment and emergency response. International Journal of Disaster Risk Reduction, 24, 12-23. Doi: https://doi.org/10.1016/j.ijdrr.2017.05.010 | |
dc.relation | Ni, C., de Souza, R., Lu, Q., & Goh, M. (2015). Emergency Preparedness of Humanitarian Organizations: A System Dynamics Approach. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 113-127. Doi: https://doi.org/10.1007/978-3-319-15455-8_7 | |
dc.relation | Nikbakhsh, E. & Farahani, R. Z. (2011). Humanitarian Logistics Planning in Disaster Relief Operations. En Farahani, R. Z., Rezapour, S., & Kardar, L. (Eds.), Logistics Operations and Management: Concepts and Models. Amsterdam: Elsevier. pp. 291-332. Doi: https://doi.org/10.1016/B978-0-12-385202-1.00015-3 | |
dc.relation | Noham, R., & Tzur, M. (2018). Designing humanitarian supply chains by incorporating actual post-disaster decisions. European Journal of Operational Research, 265 (3), 1064-1077. Doi: https://doi.org/10.1016/j.ejor.2017.08.042 | |
dc.relation | Nurmala, N., de Vries, J., & de Leeuw, S. (2018). Cross-sector humanitarian-business partnerships in managing humanitarian logistics: an empirical verification. International Journal of Production Research, 56 (21), 6842-6858. Doi: https://doi.org/10.1080/00207543.2018.1449977 | |
dc.relation | OCHA. (2012). Coordination to Save Lives - History and Emerging Challenges. United Nations Office for the Coordination of Humanitarian Affairs, Nueva York y Ginebra. Disponible en https://www.unocha.org/publication/policy-briefs-studies/coordination-save-lives-history-and-emerging-challenges. Consultado: 20. Dic. 2017. | |
dc.relation | Ochoa, A., Rudomin, I., Vargas-Solar, G., Espinosa-Oviedo, J. A., Perez, H., & Zechinelli-Martini, J. L. (2017). Humanitarian Logistics and Cultural Diversity within Crowd Simulation. Computación y Sistemas, 21 (1), 7-21. Doi: https://doi.org/10.13053/CyS-21-1-2583 | |
dc.relation | Olaya, C. (2012a). Models that include cows: the significance of operational thinking. En Proceedings of the 30th International Conference of the System Dynamics Society. St Gallen, Suiza, 22-26 Julio 2012, pp. 1-28. | |
dc.relation | Olaya, C. (2012b). The Importance of Being Atheoretical: Management as Engineering. En Groesser, S. & Zeier, R. (Eds.), Systemic Management for Intelligent Organizations: Concepts, Model-Based Approaches and Applications. Heidelberg: Springer. pp. 21-46. Doi: https://doi.org/10.1007/978-3-642-29244-6_2 | |
dc.relation | Olaya, C. (2013). Más ingeniería y menos ciencia por favor. En Proceedings of the 11th Latin American System Dynamics Conference. México D.F., México, 6-8 Noviembre 2013, pp. 1-6. | |
dc.relation | Oloruntoba, R., & Gray, R. (2006). Humanitarian aid: an agile supply chain? Supply Chain Management-An International Journal, 11 (2), 115-120. Doi: https://doi.org/10.1108/13598540610652492 | |
dc.relation | Oloruntoba, R., & Gray, R. (2009). Customer service in emergency relief chains. International Journal of Physical Distribution & Logistics Management, 39 (6), 486-505. Doi: https://doi.org/10.1108/09600030910985839 | |
dc.relation | Osorio-Ramírez, C. (2016). Mecanismos de coordinación para la optimización del desempeño de la cadena logística humanitaria mediante modelamiento estocástico. Caso colombiano. Tesis Doctoral. Universidad Nacional de Colombia, Bogotá (Colombia). | |
dc.relation | Owusu-Kwateng, K., Hamid, M. A., & Debrah, B. (2017). Disaster relief logistics operation: an insight from Ghana. International Journal of Emergency Services, 6 (1), 4-13. Doi: https://doi.org/10.1108/IJES-10-2016-0022 | |
dc.relation | Özdamar, L., & Ertem, M. A. (2015). Models, solutions and enabling technologies in humanitarian logistics. European Journal of Operational Research, 244 (1), 55-65. Doi: https://doi.org/10.1016/j.ejor.2014.11.030 | |
dc.relation | Özdamar, L., Ekinci, E., & Küçükyazici, B. (2004). Emergency logistics planning in natural disasters. Annals of Operations Research, 129 (1-4), 217-245. Doi: https://doi.org/10.1023/B:ANOR.0000030690.27939.39 | |
dc.relation | Ozguven, E. E., & Ozbay, K. (2015). An RFID-based inventory management framework for emergency relief operations. Transportation Research Part C: Emerging Technologies, 57, 166-187. Doi: https://doi.org/10.1016/j.trc.2015.06.021 | |
dc.relation | Paul, J. A., & MacDonald, L. (2016). Location and capacity allocations decisions to mitigate the impacts of unexpected disasters. European Journal of Operational Research, 251 (1), 252-263. Doi: https://doi.org/10.1016/j.ejor.2015.10.028 | |
dc.relation | Paul, J. A., & Wang, X. F. (2019). Robust location-allocation network design for earthquake preparedness. Transportation Research Part B: Methodological, 119, 139-155. Doi: https://doi.org/10.1016/j.trb.2018.11.009 | |
dc.relation | Peng, M., Chen, H., & Zhou, M. (2014b). Modelling and simulating the dynamic environmental factors in post-seismic relief operation. Journal of Simulation, 8 (2), 164-178. Doi: https://doi.org/10.1057/jos.2013.27 | |
dc.relation | Peng, M., Peng, Y., & Chen, H. (2014a). Post-seismic supply chain risk management: A system dynamics disruption analysis approach for inventory and logistics planning. Computers & Operations Research, 42, 14-24. Doi: https://doi.org/10.1016/j.cor.2013.03.003 | |
dc.relation | Pettit, S., & Beresford, A. (2009). Critical success factors in the context of humanitarian aid supply chains. International Journal of Physical Distribution & Logistics Management, 39 (6), 450-468. Doi: https://doi.org/10.1108/09600030910985811 | |
dc.relation | PNUD. (2015). Nuevos Escenarios de Cambio Climático para Colombia 2011 – 2100. Programa de las Naciones Unidas para el Desarrollo – PNUD Colombia, Bogotá. Disponible en https://reliefweb.int/report/colombia/nuevos-escenarios-de-cambio-clim-tico-para-colombia-2011-2100-herramientas-cient-0. Consultado: 1. Oct. 2020. | |
dc.relation | Pomerol, J. C., & Barba-Romero, S. (2000). Multicriterion Decision in Management: principles and practice. Boston: Kluwer Academic Publishers. | |
dc.relation | Ponte, B., Costas, J., Puche, J., Pino, R., & De la Fuente, D. (2018). The value of lead time reduction and stabilization: A comparison between traditional and collaborative supply chains. Transportation Research Part E: Logistics and Transportation Review, 111, 165-185. Doi: https://doi.org/10.1016/j.tre.2018.01.014 | |
dc.relation | Powell, J. H., Mustafee, N., Chen, A. S., & Hammond, M. (2016). System-focused risk identification and assessment for disaster preparedness: Dynamic threat analysis. European Journal of Operational Research, 254 (2), 550-564. Doi: https://doi.org/10.1016/j.ejor.2016.04.037 | |
dc.relation | Pradhananga, R., Mutlu, F., Pokharel, S., Holguín-Veras, J., & Seth, D. (2016). An integrated resource allocation and distribution model for pre-disaster planning. Computers & Industrial Engineering, 91, 229-238. Doi: https://doi.org/10.1016/j.cie.2015.11.010 | |
dc.relation | Quezada, A., & Canessa, E. (2010). Modelado basado en agentes: una herramienta para complementar el análisis de fenómenos sociales. Avances en Psicología Latinoamericana, 28 (2), 226-238. | |
dc.relation | Rachaniotis, N. P., Dasaklis, T., Pappis, C. P., & Van Wassenhove, L. N. (2013). Multiple Location and Routing Models in Humanitarian Logistics. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 43-57. Doi: https://doi.org/10.1007/978-1-4614-7007-6_3 | |
dc.relation | Raghukumar, B. R., Agarwal, A., & Sharma, M. K. (2016). An Agile and Flexible Supply Chain for Efficient Humanitarian Logistics in a Disaster Management System. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 129-139. Doi: https://doi.org/10.1007/978-81-322-2416-7_9 | |
dc.relation | Ransikarbum, K., & Mason, S. J. (2014). Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations. International Journal of Production Research, 54 (1), 49-68. Doi: https://doi.org/10.1080/00207543.2014.977458 | |
dc.relation | Regis-Hernández, F., Mora-Vargas, J., & Ruiz, A. (2017). A Multi-Criteria Vertical Coordination Framework for a Reliable Aid Distribution. Journal of Industrial Engineering and Management, 10 (4), 789-815. Doi: https://doi.org/10.3926/jiem.2253 | |
dc.relation | Rekik, M., Ruiz, A., Renaud, J., Berkoune, D., & Paquet, S. (2013). A Decision Support System for Humanitarian Network Design and Distribution Operations. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 1-20. Doi: https://doi.org/10.1007/978-1-4614-7007-6_1 | |
dc.relation | Remida, A. (2015). A Systemic Approach to Sustainable Humanitarian Logistics. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 11-29. Doi: https://doi.org/10.1007/978-3-319-15455-8_2 | |
dc.relation | Rezaei-Malek, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Bozorgi-Amiri, A. (2016). An interactive approach for designing a robust disaster relief logistics network with perishable commodities. Computers & Industrial Engineering, 94, 201-215. Doi: https://doi.org/10.1016/j.cie.2016.01.014 | |
dc.relation | Richardson, D. A., De Leeuw, S., & Dullaert, W. (2016). Factors Affecting Global Inventory Prepositioning Locations in Humanitarian Operations – A Delphi Study. Journal of Business Logistics, 37 (1), 59-74. Doi: https://doi.org/10.1111/jbl.12112 | |
dc.relation | Rodon, J., Maria-Serrano, J. F., & Giménez, C. (2012). Managing cultural conflicts for effective humanitarian aid. International Journal of Production Economics, 139 (2), 366-376. Doi: https://doi.org/10.1016/j.ijpe.2011.08.029 | |
dc.relation | Rodríguez, 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, 39 (4), 863-873. Doi: https://doi.org/10.1016/j.cor.2009.11.014 | |
dc.relation | Rodríguez-Espíndola, O., & Gaytán, J. (2015). Scenario-based preparedness plan for floods. Natural Hazards, 76 (2), 1241-1262. Doi: https://doi.org/10.1007/s11069-014-1544-2 | |
dc.relation | Rodríguez-Espíndola, O., Albores, P., & Brewster, C. (2018a). Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods. European Journal of Operational Research, 264 (3), 978-993. Doi: https://doi.org/10.1016/j.ejor.2017.01.021 | |
dc.relation | Rodríguez-Espíndola, O., Albores, P., & Brewster, C. (2018b). Dynamic formulation for humanitarian response operations incorporating multiple organisations. International Journal of Production Economics, 204, 83-98. Doi: https://doi.org/10.1016/j.ijpe.2018.07.023 | |
dc.relation | Rodríguez-Zoya, L. G., & Roggero, P. (2015). Modelos basados en agentes: aportes epistemológicos y teóricos para la investigación social. Revista Mexicana de Ciencias Políticas y Sociales, 60 (225), 227-262. Doi: https://doi.org/10.1016/S0185-1918(15)30025-8 | |
dc.relation | Rottkemper, B., Fischer, K., Blecken, A., & Danne, C. (2011). Inventory relocation for overlapping disaster settings in humanitarian operations. OR Spectrum, 33, 721-749. Doi: https://doi.org/10.1007/s00291-011-0260-5 | |
dc.relation | Saharan, V. (2015). Disaster Management and Corruption: Issues, Interventions and Strategies. En Ha, H., Fernando, R. L. S., & Mahmood, A. (Eds.), Strategic Disaster Risk Management in Asia. Nueva Delhi: Springer. pp. 193-206. Doi: https://doi.org/10.1007/978-81-322-2373-3_13 | |
dc.relation | Sahay, B. S., Menon, V. C., & Gupta, S. (2016). Humanitarian Logistics and Disaster Management: The Role of Different Stakeholders. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 3-21. Doi: https://doi.org/10.1007/978-81-322-2416-7_1 | |
dc.relation | Sahebi, I. G., Arab, A., & Moghadam, M. R. S. (2017). Analyzing the barriers to humanitarian supply chain management: A case study of the Tehran Red Crescent Societies. International Journal of Disaster Risk Reduction, 24, 232-241. Doi: https://doi.org/10.1016/j.ijdrr.2017.05.017 | |
dc.relation | Sahin, H., Kara, B. Y., & Karasan, O. E. (2016). Debris removal during disaster response: A case for Turkey. Socio-Economic Planning Sciences, 53, 49-59. Doi: https://doi.org/10.1016/j.seps.2015.10.003 | |
dc.relation | Santos, F. C., Pacheco, J. M., & Lenaerts, T. (2006). Evolutionary dynamics of social dilemmas in structured heterogeneous populations. Proceedings of the National Academy of Sciences, 103 (9), 3490-3494. Doi: https://doi.org/10.1073/pnas.0508201103 | |
dc.relation | Sarache, W., & Morales, M. M. (2016). Localización, transporte e inventarios: tres decisiones estructurales en el diseño de cadenas de abastecimiento. Bogotá: Editorial Universidad Nacional de Colombia. | |
dc.relation | Sarache, W., Cárdenas-Aguirre, D. M., & Giraldo, J. A. (2005). Procedimiento para la definición y jerarquización de prioridades competitivas de fabricación. Aplicaciones en las pymes de la industria metalmecánica. Ingeniería y Competitividad, 7 (2), 84-91. | |
dc.relation | Sarache, W., Costa-Salas, Y. J., & Martínez-Giraldo, J. P. (2015). Environmental performance evaluation under a green supply chain approach. DYNA, 82 (189), 207-215. https://doi.org/10.15446/dyna.v82n189.48550 | |
dc.relation | Sauser, B., Baldwin, C., Pourreza, S., Randall, W., & Nowicki, D. (2018). Resilience of small- and medium-sized enterprises as a correlation to community impact: an agent-based modeling approach. Natural Hazards, 90 (1), 79-99. Doi: https://doi.org/10.1007/s11069-017-3034-9 | |
dc.relation | Schaffernicht, M. (2009). Indagación de situaciones dinámicas mediante la Dinámica de Sistemas. 1a. ed. Talca, Chile: Editorial Universidad de Talca. | |
dc.relation | Scholten, K., Scott, P. S., & Fynes, B. (2014). Mitigation processes – antecedents for building supply chain resilience. Supply Chain Management: An International Journal, 19 (2), 211-228. Doi: https://doi.org/10.1108/SCM-06-2013-0191 | |
dc.relation | Schulz, S. F. (2009). Disaster Relief Logistics: Benefits of and Impediments to Horizontal Cooperation between Humanitarian Organizations. Tesis Doctoral. Technischen Universität Berlin, Berlin (Alemania). | |
dc.relation | Schulz, S. F., & Blecken, A. (2010). Horizontal cooperation in disaster relief logistics: benefits and impediments. International Journal of Physical Distribution & Logistics Management, 40 (8-9), 636-656. Doi: https://doi.org/10.1108/09600031011079300 | |
dc.relation | Sebbah, S., Boukhtouta, A., Berger, J., & Ghanmi, A. (2013). Military Logistics Planning in Humanitarian Relief Operations. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 77-110. Doi: https://doi.org/10.1007/978-1-4614-7007-6_5 | |
dc.relation | Seuring, S., Müller, M., Reiner, G., & Kotzab, H. (2005). Is There a Right Research Design for Your Supply Chain Study? En Kotzab, H., Seuring, S., Müller, M., & Reiner, G. (Eds.), Research Methodologies in Supply Chain Management. Heidelberg: Physica-Verlag. pp.1-12. Doi: https://doi.org/10.1007/3-7908-1636-1_1 | |
dc.relation | Shafiee, M. E., & Berglund, E. Z. (2016). Agent-based modeling and evolutionary computation for disseminating public advisories about hazardous material emergencies. Computers, Environment and Urban Systems, 57, 12-25. Doi: https://doi.org/10.1016/j.compenvurbsys.2016.01.001 | |
dc.relation | Shannon, R. E. (1998). Introduction to the Art and Science of Simulation. En Proceedings of the 30th Conference on Winter Simulation. Washington, D.C., USA, 13-16 Diciembre 1998, pp. 7-14. Doi: https://doi.org/10.1109/WSC.1998.744892 | |
dc.relation | Sharif, M. T., & Salari, M. (2015). A GRASP algorithm for a humanitarian relief transportation problem. Engineering Applications of Artificial Intelligence, 41, 259-269. Doi: https://doi.org/10.1016/j.engappai.2015.02.013 | |
dc.relation | Sheffi, Y. (2015). The Power of Resilience: How the Best Companies Manage the Unexpected. Cambridge, Mass.: MIT Press. | |
dc.relation | Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. J. (2008). Crowd simulation for emergency response using BDI agents based on immersive virtual reality. Simulation Modelling Practice and Theory, 16 (9), 1415-1429. Doi: https://doi.org/10.1016/j.simpat.2008.07.004 | |
dc.relation | Sheppard, A., Tatham, P., Fisher, R., & Gapp, R. (2013). Humanitarian logistics: enhancing the engagement of local populations. Journal of Humanitarian Logistics and Supply Chain Management, 3 (1), 22-36. Doi: https://doi.org/10.1108/20426741311328493 | |
dc.relation | Sheu, J. B. (2007). An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research Part E: Logistics and Transportation Review, 43 (6), 687-709. Doi: https://doi.org/10.1016/j.tre.2006.04.004 | |
dc.relation | Sheu, J. B., & Pan, C. (2015). Relief supply collaboration for emergency logistics responses to large-scale disasters. Transportmetrica A: Transport Science, 11 (3), 210-242. Doi: https://doi.org/10.1080/23249935.2014.951886 | |
dc.relation | Shoham, Y., & Leyton-Brown, K. (2008). Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge: Cambridge University Press. | |
dc.relation | Siegel, S. (1978). Estadística no paramétrica aplicada a las ciencias de la conducta. 2a. ed. México D.F.: Ed. Trillas. | |
dc.relation | Simões-Marques, M., & Nunes, I. L. (2013). A Fuzzy Multicriteria Methodology to Manage Priorities and Resource Assignment in Critical Situations. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 129-153. Doi: https://doi.org/10.1007/978-1-4614-7007-6_7 | |
dc.relation | Singh, A. (2016). Supplier Selection and Multi-period Demand Allocation in a Humanitarian Supply Chain. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 189-207. Doi: https://doi.org/10.1007/978-81-322-2416-7_14 | |
dc.relation | Singh, R. K., Gupta, A., & Gunasekaran, A. (2018). Analysing the interaction of factors for resilient humanitarian supply chain. International Journal of Production Research, 56 (21), 6809-6827. Doi: https://doi.org/10.1080/00207543.2018.1424373 | |
dc.relation | Smadi, H., Al Theeb, N., & Bawa’neh, H. (2018). Logistics system for drinking water distribution in post disaster humanitarian relief, Al-Za'atari camp. Journal of Humanitarian Logistics and Supply Chain Management, 8 (4), 477-496. Doi: https://doi.org/10.1108/JHLSCM-12-2017-0072 | |
dc.relation | Sterman, J. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: McGraw Hill. | |
dc.relation | Suárez-Moreno, J. D., Osorio-Ramírez, C., & Adarme-Jaimes, W. (2016). Agent-based model for material convergence in humanitarian logistics. Revista Facultad de Ingeniería-Universidad de Antioquia, 81, 24-34. Doi: https://doi.org/10.17533/udea.redin.n81a03 | |
dc.relation | Swanson, R. D., & Smith, R. J. (2013). A Path to a Public–Private Partnership: Commercial Logistics Concepts Applied to Disaster Response. Journal of Business Logistics, 34 (4), 335-346. Doi: https://doi.org/10.1111/jbl.12031 | |
dc.relation | Tang, C., & Tomlin, B. (2008). The power of flexibility for mitigating supply chain risks. International Journal of Production Economics, 116 (1), 12-27. Doi: https://doi.org/10.1016/j.ijpe.2008.07.008 | |
dc.relation | Tang, J., Zhu, K. J., Guo, H. X., Gong, C. Z., Liao, C., & Zhang, S. W. (2018). Using auction-based task allocation scheme for simulation optimization of search and rescue in disaster relief. Simulation Modelling Practice and Theory, 82, 132-146. Doi: https://doi.org/10.1016/j.simpat.2017.12.014 | |
dc.relation | Tang, J., Zhu, K., Guo, H., Liao, C., & Zhang, S. (2017). Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism. Algorithms, 10 (4), Número de artículo: 125, 17 páginas. Doi: https://doi.org/10.3390/a10040125 | |
dc.relation | Tatham, P., & Kovács, G. (2010). The application of "swift trust" to humanitarian logistics. International Journal of Production Economics, 126 (1), 35-45. Doi: https://doi.org/10.1016/j.ijpe.2009.10.006 | |
dc.relation | Tatham, P., & Rietjens, S.B. (2016). Integrated disaster relief logistics: A stepping stone towards viable civil-military networks? Disasters, 40 (1), 7-25. Doi: https://doi.org/10.1111/disa.12131 | |
dc.relation | Tatham, P., & Spens, K. (2011). Towards a humanitarian logistics knowledge management system. Disaster Prevention and Management, 20 (1), 6-26. Doi: https://doi.org/10.1108/09653561111111054 | |
dc.relation | Tatham, P., & Spens, K. (2016). Cracking the humanitarian logistic coordination challenge: Lessons from the urban search and rescue community. Disasters, 40 (2), 246-261. Doi: https://doi.org/10.1111/disa.12139 | |
dc.relation | Tatham, P., Spens, K., & Kovács, G. (2017). The humanitarian common logistic operating picture: a solution to the inter-agency coordination challenge. Disasters, 41 (1), 77-100. Doi: https://doi.org/10.1111/disa.12193 | |
dc.relation | Tavana, M., Abtahi, A. R., Di Caprio, D., Hashemi, R., & Yousefi-Zenouz, R. (2018). An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio-Economic Planning Sciences, 64, 21-37. Doi: https://doi.org/10.1016/j.seps.2017.12.004 | |
dc.relation | The Guardian. (2018). Quakes, mudslides, an active volcano: inside the world's riskiest city. Guardian Media Group, Londres. Disponible en https://www.theguardian.com/cities/2018/nov/08/earthquakes-mudslides-active-volcano-worlds-riskiest-city-manizales-colombia. Consultado: 30. Sep. 2020. | |
dc.relation | Thomas, A., & Kopczak, L. (2005). From logistics to supply chain management: The path forward in the humanitarian sector, white paper, Fritz Institute, San Francisco, CA. | |
dc.relation | Tian, Y., Zhou, T. S., Yao, Q., Zhang, M., & Li, J. S. (2014). Use of an Agent-Based Simulation Model to Evaluate a Mobile-Based System for Supporting Emergency Evacuation Decision Making. Journal of Medical Systems, 38 (12), Número de artículo: 149, 13 páginas. Doi: https://doi.org/10.1007/s10916-014-0149-3 | |
dc.relation | Timperio, G., Panchal, G. B., Samvedi, A., Goh, M., & De Souza, R. (2017). Decision support framework for location selection and disaster relief network design. Journal of Humanitarian Logistics and Supply Chain Management, 7 (3), 222-245. Doi: https://doi.org/10.1108/JHLSCM-11-2016-0040 | |
dc.relation | Tofighi, S., Torabi, S. A., & Mansouri, S. A. (2016). Humanitarian logistics network design under mixed uncertainty. European Journal of Operational Research, 250 (1), 239-250. Doi: https://doi.org/10.1016/j.ejor.2015.08.059 | |
dc.relation | Tomasini, R. M., & Van Wassenhove, L. N. (2009). Humanitarian Logistics. Londres: Palgrave Macmillan. | |
dc.relation | Trecarichi, G., Rizzi, V., Marchese, M., Vaccari, L., & Besana, P. (2010). Enabling information gathering patterns for emergency response with the OpenKnowledge system. Computing and Informatics, 29 (4), 537-555. | |
dc.relation | Tzeng, G. H., Cheng, H. J., & Huang, T. D. (2007). Multi-objective optimal planning for designing relief delivery systems. Transportation Research Part E: Logistics and Transportation Review, 43 (6), 673-686. Doi: https://doi.org/10.1016/j.tre.2006.10.012 | |
dc.relation | UNESCO. (2010). Engineering: Issues, Challenges and Opportunities for Development. Paris. Disponible en http://unesdoc.unesco.org/images/0018/001897/189753e.pdf. Consultado: 31. Mar. 2018. | |
dc.relation | UNGRD. (2014). Documento de priorización de líneas estratégicas y zonas de intervención en gestión del riesgo de desastres en Colombia. Unidad Nacional para la Gestión del Riesgo de Desastres, Bogotá. Disponible en http://cedir.gestiondelriesgo.gov.co/dvd/archivospdf/priorizaci%C3%B3n_ungrd.pdf. Consultado: 5. May. 2016. | |
dc.relation | UNGRD. (2018). Colombia menos vulnerable: la gestión del riesgo de desastres en nuestra historia. Unidad Nacional para la Gestión del Riesgo de Desastres, Bogotá. Disponible en https://repositorio.gestiondelriesgo.gov.co/handle/20.500.11762/27176. Consultado: 30. Sep. 2020. | |
dc.relation | UNISDR. (2004). Living with Risk. A Global Review of Disaster Reduction Initiatives. United Nations Office for Disaster Risk Reduction, Ginebra. Disponible en http://www.unisdr.org/eng/about_isdr/bd-lwr-2004-eng.htm. Consultado: 26. Feb. 2016. | |
dc.relation | UNISDR. (2015). Sendai Framework for Disaster Risk Reduction 2015 – 2030. United Nations Office for Disaster Risk Reduction, Ginebra. Disponible en https://www.unisdr.org/we/inform/publications/43291. Consultado: 14. May. 2017. | |
dc.relation | UNISDR. (2017). The secretariat of the international strategy for disaster reduction. United Nations Office for Disaster Risk Reduction, Ginebra. Disponible en http://www.unisdr.org/we/inform/terminology. Consultado: 23. Dic. 2017. | |
dc.relation | Vaillancourt, A., & Haavisto, I. (2016). Country logistics performance and disaster impact. Disasters, 40 (2), 262-283. Doi: https://doi.org/10.1111/disa.12146 | |
dc.relation | Van der Laan, E. A., de Brito, M. P., Van Fenema, P. C., & Vermaesen, S. C. (2009). Managing information cycles for intra-organisational coordination of humanitarian logistics. International Journal of Services, Technology and Management, 12 (4), 362-390. Doi: https://doi.org/10.1504/IJSTM.2009.025814 | |
dc.relation | Van Wassenhove, L. N. (2006). Humanitarian aid logistics: supply chain management in high gear. Journal of the Operational Research Society, 57 (5), 475-489. Doi: https://doi.org/10.1057/palgrave.jors.2602125 | |
dc.relation | Vega, D., & Roussat, C. (2015). Humanitarian logistics: the role of logistics service providers. International Journal of Physical Distribution & Logistics Management, 45 (4), 352-375. Doi: https://doi.org/10.1108/IJPDLM-12-2014-0309 | |
dc.relation | Verma, A., & Gaukler, G. M. (2015). Pre-positioning disaster response facilities at safe locations: An evaluation of deterministic and stochastic modeling approaches. Computers & Operations Research, 62, 197-209. Doi: https://doi.org/10.1016/j.cor.2014.10.006 | |
dc.relation | Vitoriano, B., Rodríguez, J. T., Tirado, G., Martín-Campo, J. M., Ortuño, M. T., & Montero, J. (2015). Intelligent Decision-Making Models for Disaster Management. Human and Ecological Risk Assessment: An International Journal, 21 (5), 1341-1360. Doi: https://doi.org/10.1080/10807039.2014.957947 | |
dc.relation | Von Bertalanffy, L. (1976). Teoría General de los Sistemas. México D.F.: Fondo de Cultura Económica. | |
dc.relation | Voyer, J., Dean, M. D., & Pickles, C. B. (2016). Hospital evacuation in disasters: uncovering the systemic leverage using system dynamics. International Journal of Emergency Management, 12 (2), 152-167. | |
dc.relation | Wallace, R., Geller, A., & Ogawa, V. A. (2015). Assessing the Use of Agent-Based Models for Tobacco Regulation. Washington, D.C.: The National Academies Press. | |
dc.relation | Wang, Z. L., & Zhang, J. H. (2019). Agent-based evaluation of humanitarian relief goods supply capability. International Journal of Disaster Risk Reduction, 36, Número de artículo: 101105, 11 páginas. Doi: https://doi.org/10.1016/j.ijdrr.2019.101105 | |
dc.relation | Wei, X., Al-Refaie, A., Robles, M., & Noche, B. (2015). A Sustainable Humanitarian Relief Network Study for the Wenchuan Earthquake. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 193-213. Doi: https://doi.org/10.1007/978-3-319-15455-8_11 | |
dc.relation | Wilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: Modeling natural, social and engineered complex systems with NetLogo. Cambridge: MIT Press. | |
dc.relation | Wilson, M. M. J., Tatham, P., Payne, J., L'Hermitte, C., & Shapland, M. (2018). Best practice relief supply for emergency services in a developed economy: Evidence from Queensland Australia. Journal of Humanitarian Logistics and Supply Chain Management, 8 (1), 107-132. Doi: https://doi.org/10.1108/JHLSCM-03-2017-0008 | |
dc.relation | Xanthopoulos, A. S., & Koulouriotis, D. E. (2013). A Multi-agent Based Framework for Vehicle Routing in Relief Delivery Systems. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 167-182. Doi: https://doi.org/10.1007/978-1-4614-7007-6_9 | |
dc.relation | Xu, J. P., Dai, J. Z., Rao, R. Q., & Xie, H. D. (2016). Critical Systems Thinking on the Inefficiency in Post-Earthquake Relief: A Practice in Longmen Shan Fault Area. Systemic Practice and Action Research, 29 (5), 425-448. Doi: https://doi.org/10.1007/s11213-016-9374-7 | |
dc.relation | Xu, L., & Beamon, B. M. (2006). Supply chain coordination and cooperation mechanisms: An attribute-based approach. Journal of Supply Chain Management, 42 (1), 4-12. Doi: https://doi.org/10.1111/j.1745-493X.2006.04201002.x | |
dc.relation | Yadav, D. K., & Barve, A. (2015). Analysis of critical success factors of humanitarian supply chain: An application of Interpretive Structural Modeling. International Journal of Disaster Risk Reduction, 12, 213-225. Doi: https://doi.org/10.1016/j.ijdrr.2015.01.008 | |
dc.relation | Yao, X., Huang, R. T., Song, M. L., & Mishra, N. (2018). Pre-positioning inventory and service outsourcing of relief material supply chain. International Journal of Production Research, 56 (21), 6859-6871. Doi: https://doi.org/10.1080/00207543.2018.1495853 | |
dc.relation | Yi, W., & Özdamar, L. (2007). A dynamic logistics coordination model for evacuation and support in disaster response activities. European Journal of Operational Research, 179 (3), 1177-1193. Doi: https://doi.org/10.1016/j.ejor.2005.03.077 | |
dc.relation | Zagorecki, A., Ko, K., & Comfort, L. K. (2010). Interorganizational Information Exchange and Efficiency: Organizational Performance in Emergency Environments. JASSS-The Journal of Artificial Societies and Social Simulation, 13 (3), Número de artículo: 3, 6 páginas. Doi: https://doi.org/10.18564/jasss.1589 | |
dc.relation | Zhao, K., Yen, J., Ngamassi, L. M., Maitland, C., & Tapia, A. H. (2012). Simulating inter-organizational collaboration network: a multi-relational and event-based approach. Simulation-Transactions of The Society for Modeling and Simulation International, 88 (5), 617-633. Doi: https://doi.org/10.1177/0037549711421942 | |
dc.relation | Zhu, K. J., Tang, J., Guo, H. X., Gong, C. Z., & Li, J. L. (2018). Using a combinatorial auction-based approach for simulation of cooperative rescue operations in disaster relief. International Journal of Modeling Simulation and Scientific Computing, 9 (4), Número de artículo: 1850035, 21 páginas. Doi: https://doi.org/10.1142/S1793962318500356 | |
dc.rights | Atribución-SinDerivadas 4.0 Internacional | |
dc.rights | http://creativecommons.org/licenses/by-nd/4.0/ | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.title | La coordinación inter-organizacional en los procesos logísticos de preparación de emergencias y desastres. | |
dc.type | Tesis | |