Mostrar el registro sencillo del ítem

Análisis de la relación entre políticas de asignación de recursos en la atención de desastres y la mortalidad

dc.contributor.advisorGonzález Rodríguez, Leonardo José
dc.contributor.authorGonzález Forero, María Catalina
dc.date.accessioned2014-02-04T22:22:12Z
dc.date.available2014-02-04T22:22:12Z
dc.date.created2014-02-04
dc.date.issued2013
dc.identifier.citationAltay, N., & Green III, W. G. (2006). OR/MS research in disaster operations management. European Journal of Operational Research, 175(1), 475-493.
dc.identifier.citationAtli, O. (2011). Tabu Search and an Exact Algorithm for the Solutions of Resource-Constrained Project Scheduling Problems. International Journal of Computational Intelligence Systems, 4(2), 255–267.
dc.identifier.citationAtli, O., & Kahraman, C. (2012). Fuzzy Resource-Constrained Project Scheduling Using Taboo Search Algorithm. International Journal of Intelligent Systems, 27, 873–907. doi:10.1002/int
dc.identifier.citationBalcik, B., Beamon, B. M., Krejci, C. C., Muramatsu, K. M., & Ramirez, M. (2010). Coordination in humanitarian releaf chains: Practices, challenges and opportunities. Int. J. Production Economics, 126, 22-34.
dc.identifier.citationBallestin González, F. (2002). Tesis Doctoral. Nuevos métodos de resolución del problema de secuenciación de proyectos con recursos limitados.
dc.identifier.citationBallestín, F., & Blanco, R. (2011). Theoretical and practical fundamentals for multi-objective optimisation in resource-constrained project scheduling problems. Computers & Operations Research, 38(1), 51–62. doi:10.1016/j.cor.2010.02.004
dc.identifier.citationBaradaran, S., Fatemi Ghomi, S. M. T., Mobini, M., & Hashemin, S. S. (2010). A hybrid scatter search approach for resource-constrained project scheduling problem in PERT-type networks. Advances in Engineering Software, 41(7-8), 966–975. doi:10.1016/j.advengsoft.2010.05.010
dc.identifier.citationBaradaran, S., Fatemi Ghomi, S. M. T., Ranjbar, M., & Hashemin, S. S. (2012). Multi-mode renewable resource-constrained allocation in PERT networks. Applied Soft Computing, 12(1), 82–90. doi:10.1016/j.asoc.2011.09.007
dc.identifier.citationBarrios, A., Ballestín, F., & Valls, V. (2011). A double genetic algorithm for the MRCPSP/max. Computers & Operations Research, 38(1), 33–43. doi:10.1016/j.cor.2009.09.019
dc.identifier.citationBartels, J.-H., Gather, T., & Zimmermann, J. (2011). Dismantling of nuclear power plants at optimal NPV. Annals of Operations Research, 186(1), 407–427. doi:10.1007/s10479-010-0788-9
dc.identifier.citationBhaskar, T., Pal, M. N., & Pal, A. K. (2011). A heuristic method for RCPSP with fuzzy activity times. European Journal Of Operational Research, 208(1), 57–66. doi:10.1016/j.ejor.2010.07.021
dc.identifier.citationBlecken, A. (2009). “A Reference Task Model for Supply Chain Processes of Humanitarian Organisations”. Dissertation, Paderborn University.
dc.identifier.citationBianco, L., & Caramia, M. (2010). A new lower bound for the resource-constrained project scheduling problem with generalized precedence relations. Computers & Operations Research, 38, 14–20. doi:10.1016/j.cor.2009.07.003
dc.identifier.citationBianco, L., & Caramia, M. (2012). An exact algorithm to minimize the makespan in project scheduling with scarce resources and generalized precedence relations. European Journal of Operational Research, 219(1), 73–85. doi:10.1016/j.ejor.2011.12.019
dc.identifier.citationBrowning, T. R., & Yassine, A. A., (2010a), “Resource-constrained multi-project scheduling: Priority rule performance revisited”, International Journal of Production Economics, 126(2), pg. 212– 228.
dc.identifier.citationBrowning, T. R., & Yassine, A. A., (2010b), “A random generator of resource-constrained multi-project network problems”, Journal of Scheduling, 13(2), pg. 143–161.
dc.identifier.citationBruni, M. E., Beraldi, P., Guerriero, F., & Pinto, E. (2011). A heuristic approach for resource constrained project scheduling with uncertain activity durations. Computers & Operations Research, 38(9), 1305–1318. doi:10.1016/j.cor.2010.12.004
dc.identifier.citationČapek, R., Šůcha, P., & Hanzálek, Z. (2012). Production scheduling with alternative process plans. European Journal of Operational Research, 217, 300–311. doi:10.1016/j.ejor.2011.09.018
dc.identifier.citationChandes, J., & Paché, G. (2009). Investigating humanitarian logistics issues: from operations management to strategic action. Journal of Manufacturing Technology and Management, 21(3), 320-340.
dc.identifier.citationChen, R.-M. (2011). Particle swarm optimization with justification and designed mechanisms for resource-constrained project scheduling problem. Expert Systems with Applications, 38(6), 7102–7111. doi:10.1016/j.eswa.2010.12.059
dc.identifier.citationChen, W., Shi, Y., Teng, H., Lan, X., & Hu, L. (2010). An efficient hybrid algorithm for resourceconstrained project scheduling. Information Sciences, 180(6), 1031–1039. doi:10.1016/j.ins.2009.11.044
dc.identifier.citationCoelho, J., & Vanhoucke, M. (2011). Multi-mode resource-constrained project scheduling using RCPSP and SAT solvers. European Journal Of Operational Research, 213(1), 73–82. doi:10.1016/j.ejor.2011.03.019
dc.identifier.citationde la Torre, L. E., Dolinskaya, I. S., & Smilowitz, K. R. (2012). Disaster relief routin: Integrating research and practice. Socio-Economic Planning Sciences, 88-97.
dc.identifier.citationRepública de Colombia. Decreto 4147, R. (2011). Ley 4147.
dc.identifier.citationDeblaere, F., Demeulemeester, E., & Herroelen, W. (2011). Proactive policies for the stochastic resource-constrained project scheduling problem. European Journal Of Operational Research, 214(2), 308–316. doi:10.1016/j.ejor.2011.04.019
dc.identifier.citationDeblaere, F., Demeulemeester, E., & Herroelen, W. (2011b). Reactive scheduling in the multi-mode RCPSP. Computers & Operations Research, 38(1), 63–74. doi:10.1016/j.cor.2010.01.001
dc.identifier.citationDemeulemeester, E., & Herroelen, W., (2002), “Scope and Relevance of Project scheduling”, Project Scheduling, a Research Handbook, Kluwer Academic Publisher: New York, Boston, Dordrecht, London, Moscow.
dc.identifier.citationDeng, L., Lin, Y., & Chen, M. (2010). Hybrid ant colony optimization for the resource-constrained project scheduling problem. (Array, Ed.) Journal of Systems Engineering and Electronics, 21, 67–71. doi:10.3969/j.issn.1004-4132.2010.01.012
dc.identifier.citationDepartament of Defense. (s.f.). Joint Vision 2020 . Recuperado el 10 de septiembre de 2011, de http://www.dtic.mil/jointvision/jvpub2.htm
dc.identifier.citationDNP, Departamento Nacional de Planeación (2000). Recuperado de https://www.dnp.gov.co/Portals/0/archivos/documentos/GCRP/PND/Pastrana2_Reconstruccio n_Eje_Cafetero.pdf, en Febrero de 2013
dc.identifier.citationElloumi, S., & Fortemps, P. (2010). A hybrid rank-based evolutionary algorithm applied to multi-mode resource-constrained project scheduling problem. European Journal of Operational Research, 205(1), 31–41. doi:10.1016/j.ejor.2009.12.014
dc.identifier.citationElshaer, R., & Yamamoto, H. (2012). New Proactive Time Buffer Heuristics for Robust Project Scheduling. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 6(5), 559– 571. doi:10.1299/jamdsm.6.559
dc.identifier.citationElnashai, A. S., Gencturk, B., Know, O.-S., Hashash, Y. M., Kim, S. J., Jeong, S.-H., y otros. (2012). The maule (Chile) earthquake of february 27, 2010: Development of hazard, site specific ground motions and back-analysis of structures. Soil Dynamics and Earthquake Engineering, 229-245.
dc.identifier.citationElsayed, E.A. (1982). Algorithms for project scheduling with resource constraints. International Journal of Production Research, 20(1), 95–103.
dc.identifier.citationEstay Niculcar, C., Álvarez, R., & Vera, A. (2011). Material de Clase, Fundación Universitaria Iberoamericana. Asignatura: Introducción a la Gestión de Proyectos
dc.identifier.citation(EURO), A. o. (2011). Association of European Operational Research Societies. Recuperado el 27 de 10 de 2012, de EURO: http://www.euro-online.org
dc.identifier.citationFang, C., & Wang, L. (2012). An effective shuffled frog-leaping algorithm for resource-constrained project scheduling problem. Computers & Operations Research, 39(5), 890–901. doi:10.1016/j.cor.2011.07.010
dc.identifier.citationForrester, J. (1961). Industrial Dynamics. Cambridge: MA: Productivity Press.
dc.identifier.citationFredley, M. L. (2001). Disertación Doctoral. A decomposition approach for the multi.modal, resourceconstrained multi-project scheduling problem with generalized precedence and expediting resources.
dc.identifier.citationFu, N., Lau, H. C., Varakantham, P., & Xiao, F. (2012). Robust Local Search for Solving RCPSP / max with Durational Uncertainty. Journal of Artificial Intelligence Research, 43, 43–86.
dc.identifier.citationGafarov, E. R., Lazarev, A. a., & Werner, F. (2012). Approximability results for the resourceconstrained project scheduling problem with a single type of resources. Annals of Operations Research, 1–16. doi:10.1007/s10479-012-1106-5
dc.identifier.citationGermán, C. E. (2001). Protocolos Operativos de Busqueda y Rescate. Bogota, Colombia: Sistema Nacional para la Prevención y Atención de Desastres
dc.identifier.citationGobierno de Haití. (2012). Plan de Acción para la Recuperación y el Desarrollo de Haití. Recuperado de http://whc.unesco.org/uploads/activities/documents/activity-651-7.pdf, en Septiembre 8, 2012.
dc.identifier.citationGoldratt, E.M. (1997), Critical Chain, The North River Press, Great Barrington, U.S.A.
dc.identifier.citationGonzalez, L. J., Kalenatic, D., & Moreno, K. V. (2012). Metodología integral y dinámica aplicada a la programación y control de proyectos. Revista Facultad de Ingeniería Universidad de Antioquia, 31-42
dc.identifier.citationGonzalo A. (2000). Acciones para la reconstrucción del eje cafetero: Memoria Colectiva de un proceso. Recuperado de http://www.federaciondecafeteros.org/static/files/Acciones%20para%20la%20reconstrucci%C3 %B3n%20del%20eje%20cafetero%20memoria%20colectiva%20de%20un%20proceso%20- %20Gonzalo%20Valencia.pdf, en Septiembre de 2013
dc.identifier.citationGuanxiang, Z., Zhang, M., Zhiyong, Z., & Guihai, L. (2010). An Evaluation Model for Emergency Logistics System. Management and Service Science (MASS), International Conference (págs. 1-4). Wuhan: IEEE.
dc.identifier.citationHao, Q., Shen, W., Xue, Y., & Wang, S. (2010). Task network-based project dynamic scheduling and schedule coordination. Advanced Engineering Informatics, 24(4), 417–427. doi:10.1016/j.aei.2010.07.001
dc.identifier.citationHartmann, S., & Briskorn, D. (2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal Of Operational Research, 207(1), 1–14. doi:10.1016/j.ejor.2009.11.005
dc.identifier.citationHaouari, M., Kooli, A., & Néron, E., (2012), “Enhanced energetic reasoning-based lower bounds for the resource constrained project scheduling problem”, Computers & Operations Research, 39(5), 1187–1194.
dc.identifier.citationHorbach, A. (2010). A Boolean satisfiability approach to the resource-constrained project scheduling problem. Annals of Operations Research, 181, 89–107. doi:10.1007/s10479-010-0693-2
dc.identifier.citationHurink, J. L., Kok, a. L., Paulus, J. J., & Schutten, J. M. J. (2011). Time-constrained project scheduling with adjacent resources. Computers & Operations Research, 38(1), 310–319. doi:10.1016/j.cor.2010.05.006
dc.identifier.citationISO (1990), International Standard ISO/CD 8402-1 Quality Concepts and Terminology Part One: Generic Terms and Definitions, International Organization for Standardization, December
dc.identifier.citationJiuh Biing, S. (2006). An emergency logistics destribution approach for quick response to urgent relief demand in disasters. Transportation Research, 687-709.
dc.identifier.citationJu, C., & Chen, T., (2012), “Simplifying Multiproject Scheduling Problem Based on Design Structure Matrix and Its Solution by an Improved aiNet Algorithm”, Discrete Dynamics in Nature and Society, 2012, 1–22.
dc.identifier.citationKazemipoor, H., Tavakkoli-Moghaddam, R., Shahnazari-Shahrezaei, P., & Azaron, a. (2012). A differential evolution algorithm to solve multi-skilled project portfolio scheduling problems. The International Journal of Advanced Manufacturing Technology, 64(5-8), 1099–1111. doi:10.1007/s00170-012-4045-z
dc.identifier.citationKalenatic, D. (2001). Tesis Doctoral. Modelo Integrak y Dinamico para el Análisis, Planeación, Programación y Control de las Capacidades Productivas en Empresas Manufactureras. Universidad Distrital.
dc.identifier.citationKalenatic, D., González, L., Lopez, C. A., & Arias, L. (2009). El sistema de gestión tecnológica como parte del sistema logístico en la era del conocimiento. Cuadernos de Administración, 22(39), 257-286.
dc.identifier.citationKalenatic, D., Mancera Mendez, L. H., Moreno Valbuena, K. V., & González Rodriguez, L. J. (2011). Metodología de planeación logística basada en gestión de proyectos y dinámica de sistemas en empresas prestadoras de servicios. Ingenieria Universidad de Antioquia, 58, 208-218
dc.identifier.citationKhalilzadeh, M., Kianfar, F., Shirzadeh Chaleshtari, A., Shadrokh, S., & Ranjbar, M. (2012). A Modified PSO Algorithm for Minimizing the Total Costs of Resources in MRCPSP. Mathematical Problems in Engineering, 2012, 1–18. doi:10.1155/2012/365697
dc.identifier.citationKlimek, M., & Łebkowski, P. (2011). Resource allocation for robust project scheduling. Bulletin of the Polish Academy of Sciences: Technical Sciences, 59(1), 51–55. doi:10.2478/v10175-011- 0008-z
dc.identifier.citationKnust, S. (2010). Scheduling non-professional table-tennis leagues. European Journal of Operational Research, 200(2), 358–367. doi:10.1016/j.ejor.2009.01.015
dc.identifier.citationKoné, O., Artigues, C., Lopez, P., & Mongeau, M. (2011). Event-based MILP models for resourceconstrained project scheduling problems. Computers & Operations Research, 38(1), 3–13. doi:10.1016/j.cor.2009.12.011
dc.identifier.citationKooli, A., Haouari, M., Hidri, L., & Neron, E. (2010). IP-Based Energetic Reasoning for the Resource Constrained Project Scheduling Problem. Electronic Notes in Discrete Mathematics, 36, 359– 366. doi:10.1016/j.endm.2010.05.046
dc.identifier.citationKovács, G., & Spens, K. M. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution & Logistics Management, 37(2), 99-117
dc.identifier.citationKovacs, G., & Spens, K. M. (2008). Northem lights in logistics and supply chain management. Press., Copenhaue: Copenhaue Business School, págs. 217-232.
dc.identifier.citationKovács, G., & Spens, K. M. (2009). Identifying challenges in humanitarian logistics. International Journal of Physical Distribution & Logistics Management, 39(6), 506-528.
dc.identifier.citationKovács, G., & Spens, K. M. (2011). Trends and developments in Humanitarian logistics - a gap analysis. International Journal of Physical Distribution & Logistic Management, 41(1), 32-46.
dc.identifier.citationKurtulus, I., & Davis, E. W., (1982), “Multi-Project Scheduling: Categorization of Heuristic Rules Performance”, Management Science, 28(2), 161–172.
dc.identifier.citationKyriakidis, T. S., Kopanos, G. M., & Georgiadis, M. C. (2012). MILP formulations for single- and multimode resource-constrained project scheduling problems. Computers & Chemical Engineering, 36, 369–385. doi:10.1016/j.compchemeng.2011.06.007
dc.identifier.citationLambrechts, O., Demeulemeester, E., & Herroelen, W. (2011). Time slack-based techniques for robust project scheduling subject to resource uncertainty. Annals of Operations Research, 186(1), 443–464. doi:10.1007/s10479-010-0777-z
dc.identifier.citationLi, H., & Womer, K. (2012). Optimizing the Supply Chain Configuration for Make-to-Order Manufacturing. European Journal Of Operational Research, 221(1), 118–128. doi:10.1016/j.ejor.2012.03.025
dc.identifier.citationLi, S., Jia, Y., & Wang, J. (2012). A discrete-event simulation approach with multiple-comparison procedure for stochastic resource-constrained project scheduling. The International Journal of Advanced Manufacturing Technology, 63(1-4), 65–76. doi:10.1007/s00170-011-3885-2
dc.identifier.citationLiao, T. W., Egbelu, P. J., Sarker, B. R., & Leu, S. S. (2011). Metaheuristics for project and construction management – A state-of-the-art review. Automation in Construction, 20(5), 491– 505. doi:10.1016/j.autcon.2010.12.006
dc.identifier.citationLim, A., Ma, H., Rodrigues, B., Teck Tan, S., & Xiao, F. (2011). New concepts for activity float in resource-constrained project management. Computers & Operations Research, 38(6), 917– 930. doi:10.1016/j.cor.2010.10.004
dc.identifier.citationLombardi, M., & Milano, M., (2012), “A min-flow algorithm for Minimal Critical Set detection in Resource Constrained Project Scheduling”, Artificial Intelligence, 182-183, 58–67.
dc.identifier.citationMasmoudi, M., & Haït, A. (2013). Project scheduling under uncertainty using fuzzy modelling and solving techniques. Engineering Applications of Artificial Intelligence, 26(1), 135–149. doi:10.1016/j.engappai.2012.07.012
dc.identifier.citationMintzberg, H., & Waters, J. (1985). Of strategies, deliberate and emergent. Strategic Management Journal, 6, 257-272.
dc.identifier.citationMobini, M., Mobini, Z., & Rabbani, M. (2011). An Artificial Immune Algorithm for the project scheduling problem under resource constraints. Applied Soft Computing, 11(2), 1975–1982. doi:10.1016/j.asoc.2010.06.013
dc.identifier.citationMontoya-Torres, J. R., Gutierrez-Franco, E., & Pirachicán-Mayorga, C. (2010). Project scheduling with limited resources using a genetic algorithm. International Journal of Project Management, 28(6), 619–628. doi:10.1016/j.ijproman.2009.10.003
dc.identifier.citationMoreno, K. V. (Octubre de 2012). Análisis de la relación entre estrategias de gestión logística humanitaria y el tiempo de respuesta en la atención de desastres, por medio de la metodología integral y dinámica. Chía, Cundinamarca, Colombia: Tesis de Maestría Universidad de La Sabana.
dc.identifier.citationOloruntoba, R., & Gray, R. (2006). Humanitarian aid: an agile supply chain? Supply Chain Management, 11(2), 115-120.
dc.identifier.citationOnesime, O. C. T., Xu, X., & Zhan, D. (2004). a Decision Support System for Supplier Selection Process. International Journal of Information Technology & Decision Making, 03(03), 453–470
dc.identifier.citationOPS-Organización Panamericana de la Salud (1996). Establecimiento de un sistema de atención de víctimas en masa. Recuperado de http://www.proteccioncivil.gob.mx/work/models/ProteccionCivil/Resource/59/2/images/esavm.p df, en Septiembre de 2013
dc.identifier.citationOPS-Organización Panamericana de la Salud (2000). Manual para el manejo logístico de suministros humanitarios. Recuperado de http://cidbimena.desastres.hn/docum/ops/libros/manejologistico.pdf, en Enero de 2013
dc.identifier.citationParaskevopoulos, D. C., Tarantilis, C. D., & Ioannou, G. (2012). Solving project scheduling problems with resource constraints via an event list-based evolutionary algorithm. Expert Systems with Applications, 39(4), 3983–3994. doi:10.1016/j.eswa.2011.09.062
dc.identifier.citationPeteghem, V. Van, & Vanhoucke, M. (2010). A genetic algorithm for the preemptive and nonpreemptive multi-mode resource-constrained project scheduling problem. European Journal Of Operational Research, 201, 409–418. doi:10.1016/j.ejor.2009.03.034
dc.identifier.citationPettit, 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.
dc.identifier.citationPMBOK®. A guide to Project Management Body of Knowledge (2000). Recuperado de http://www.cs.bilkent.edu.tr/~cagatay/cs413/PMBOK.pdf, en Septiembre de 2013
dc.identifier.citationProject Management Institute, P. M. (2001). Practice standar for Work Breackdown Structure (WBS). Institute Project Management, Pensilvania
dc.identifier.citationQuintanilla, S., Pérez, Á., Lino, P., & Valls, V. (2012). Time and work generalised precedence relationships in project scheduling with pre-emption: An application to the management of Service Centres. European Journal of Operational Research, 219(1), 59–72. doi:10.1016/j.ejor.2011.12.018
dc.identifier.citationRanjbar, M., Khalilzadeh, M., Kianfar, F., & Etminani, K. (2012). An optimal procedure for minimizing total weighted resource tardiness penalty costs in the resource-constrained project scheduling problem. Computers & Industrial Engineering, 62(1), 264–270. doi:10.1016/j.cie.2011.09.013
dc.identifier.citationRodríguez, A., & Terry, B., (2004). Atenciones medicas urgentes y lesiones fatales como consecuencia del terremoto en Armenia, Colombia. Recuperado en Septiembre de 2013 de http://bvs.sld.cu/revistas/hie/vol43_1_05/hie06105.htm
dc.identifier.citationRodrigues, S. B., & Yamashita, D. S. (2010). An exact algorithm for minimizing resource availability costs in project scheduling. European Journal of Operational Research, 206(3), 562–568. doi:10.1016/j.ejor.2010.03.008
dc.identifier.citationSancho, R. (1990). Indicadores bibliométricos utilizados en la evaluación de la ciencia y la tecnología. Revisión bibliográfica. Revista española de Documentación científica, 13 (3-4), 842–865.
dc.identifier.citationSheu, 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:10.1016/j.tre.2006.04.004
dc.identifier.citationSchmidt, G., & Wilhem, W. E. (2000). Strategic, tactical and operational decisions in multi-national logistics networks: a review and discussion of modelling issues. International Journal of Production Research, 38(7), 1501-15023.
dc.identifier.citationSchwindt, C. (2005). Rosource Allocation in Project Management. GOR Publications.
dc.identifier.citationShi, Y., Shen, G.-J., & Chen, W. (2011). Solving Project Scheduling Problems using Estimation of Distribution Algorithm with local Simplex Search. Information Technology Journal, 10, 1374– 1380
dc.identifier.citationSheu, J.-B. (2007), “An emergency logistics distribution approach for quick response to urgent relief demand in disasters”, Transportation Research Part E, 43(6), 687–709.
dc.identifier.citationSNPAD. (2006). Guia de Actuación y Protocolos de alto Gobierno en caso de un Desastre Súbito de cobertura Nacional. Sistema Nacional para la Prevención y Atención de Desastres. Recuperado de http://www.cridlac.org/cd/cd_bivapad/pdf/doc289/doc289.htm, en Noviembre de 2012.
dc.identifier.citationSterman, J. (1994). Learning In and About Complex Systems. System Dynamics Review, 10, 291- 330.
dc.identifier.citationS.Elnashai, A., BoraGencturk, Oh-SungKwon, M.A.Hashash, Y., SungJigKim, Jeong, S.-H., y otros. (2012). The Maule (Chile) earthquake of February 27, 2010: Development of hazard, site specific ground motions and back-analysis of structures. Soil Dynamics and Earthquake Engineering, 229-245.
dc.identifier.citationTasan, S. O., & Gen, M. (2012). An integrated selection and scheduling for large-sized disjunctive network problems. 40th International Conference on Computers and Industrial Engineering CIE 2010, Article in Press. doi:10.1016/j.cie.2011.12.022
dc.identifier.citationTenrox. (2012). Tenrox. Recuperado el 20 de Octubre de 2012, de Cloud-based Project Management Software - online resource management, resource scheduling, project planning, time & expense tracking, project billing & cost reporting: http://www.tenrox.com/
dc.identifier.citationThomas, A., & L., K. (2005). From Logistics To Supply Chain Management: The Path Forward In The Humanitarian Sector. Instituto Fritz, 1-15
dc.identifier.citationThomas, A., & Mizushima, M. (2005). Logistics Training: Necessity or Luxury. Forced Migration Review, 22, 60-61.
dc.identifier.citationTomasini, R. M., & Van Wassenhove, L. N. (2004). A framework to unravel,prioritize and coordinate vulnerability and complexity factors affecting a humanitarian response operation. INSEAD, Faculty and Research, 1-15.
dc.identifier.citationUlusoy, G., & Ozdamar, L. (1989). Heuristic Performance and Network / Resource Characteristics in Resource-constrained Project Scheduling. Journal of the Operational Research Society, 40(12), 1145–1152.
dc.identifier.citationUNGRD, U. d. (2011). UNGRD. Recuperado el 30 de 10 de 2012, de UNGRD: http://www.signad.gov.co
dc.identifier.citationVan Wassenhove, L. N. (2006). Blackett Memorial Lecturew Humanitarian aid logistics: supply chain management in high gear. Journal of the Operational Research Society, 57, 475-489.
dc.identifier.citationVan Wassenhove, L. N., & Pedraza Martinez, A. J. (2012). Using OR to adapt supply chain management best practices to humanitarian logistics. International Transactions in Operational Research, 307-322.
dc.identifier.citationVitoriano, B., Ortuño, M. T., Tirado, G., & Montero, J. (2010). A multi-criteria optimization model for humanitarian aid distribution. Springer Science+Business Media, LLC.
dc.identifier.citationWaligóra, G. (2011, November 15). Discrete-continuous project scheduling with discounted cash inflows and various payment models—a review of recent results. Annals of Operations Research. doi:10.1007/s10479-011-1014-0
dc.identifier.citationWang, L., & Fang, C. (2010). An effective estimation of distribution algorithm for the multi-mode resource-constrained project scheduling problem. Control and Decision Conference CCDC 2010 Chinese, 39(2), 449–460. doi:10.1016/j.cor.2011.05.008
dc.identifier.citationWang, L., & Fang, C. (2011). An effective shuffled frog-leaping algorithm for multi-mode resourceconstrained project scheduling problem. Information Sciences, 181(2), 4804–4822. doi:10.1016/j.ins.2011.06.014
dc.identifier.citationWang, L., & Fang, C. (2012). A hybrid estimation of distribution algorithm for solving the resourceconstrained project scheduling problem. Expert Systems with Applications, 39(3), 2451–2460. doi:10.1016/j.eswa.2011.08.095
dc.identifier.citationWauters, T., Verbeeck, K., Verstraete, P., Vanden Berghe, G., & De Causmaecker, P. (2012). Realworld production scheduling for the food industry: An integrated approach. Engineering Applications of Artificial Intelligence, 25, 222–228. doi:10.1016/j.engappai.2011.05.002
dc.identifier.citationWu, S., Wan, H.-D., Shukla, S. K., & Li, B. (2011). Chaos-based improved immune algorithm (CBIIA) for resource-constrained project scheduling problems. Expert Systems with Applications, 38(4), 3387–3395. doi:10.1016/j.eswa.2010.08.124
dc.identifier.citationWuliang, P., & H, X. (2012). The Scheduling Problem of Active Critical Method. Information Technology Journal, 11, 829–839.
dc.identifier.citationXiong, J., Chen, Y., Yang, K., Zhao, Q., & Xing, L. (2012). A Hybrid Multiobjective Genetic Algorithm for Robust Resource-Constrained Project Scheduling with Stochastic Durations. Mathematical Problems in Engineering, 2012, 1–24. doi:10.1155/2012/786923
dc.identifier.citationYan, L., Jinsong, B., Xiaofeng, H., & Ye, J. (2009), “A heuristic project scheduling approach for quick response to maritime disaster rescue”, International Journal of Project Management, 27(6), 620–628.
dc.identifier.citationZamani, R. (2010). A parallel complete anytime procedure for project scheduling under multiple resource constraints. The International Journal of Advanced Manufacturing Technology, 50(1- 4), 353–362. doi:10.1007/s00170-009-2483-z
dc.identifier.citationZee Woon Lee, David N. Ford, Nitin Joglekar. (2007) Effects of resource allocation policies for reducing project durations: a systems modelling approach. Systems Research and Behavioral Science 24:6, 551-566
dc.identifier.citationZhang, L., Zou, X., & Chen, X., (2012), “Resource-constrained Scheduling in Repetitive Projects”, International Journal on Advances in Information Sciences and Service Sciences, 4(14), 287– 294.
dc.identifier.citationZiarati, K., Akbari, R., & Zeighami, V. (2011). On the performance of bee algorithms for resourceconstrained project scheduling problem. Applied Soft Computing, 11(4), 3720–3733. doi:10.1016/j.asoc.2011.02.002
dc.identifier.urihttp://hdl.handle.net/10818/9761
dc.description244 páginas
dc.description.abstractEl presente trabajo encuentra la relación entre políticas de asignación de recursos para el sistema logístico humanitario colombiano y el tiempo de respuesta del sistema para la atención de la población afectada. La relación se determina comparando el desempeño del sistema frente a dos políticas de asignación de recursos utilizadas en la programación de proyectos con recursos restringidos, identificadas como más relevantes en la literatura y adoptables al sistema humanitario. Se construyó un modelo del sistema Colombiano de atención de desastres utilizando una combinación de redes AON y dinámica de sistemas, con el fin de establecer el impacto sobre los tiempos de respuesta de dichas políticas. Se encontró que, si bien la aplicación de políticas de asignación de recursos puede cambiar significativamente el número de muertos de un desastre, las políticas evaluadas, en promedio no disminuyeron el número de muertos. El criterio de asignación de recursos utilizado actualmente por el sistema colombiano puede considerarse adecuado, pero se recomienda evaluar otras políticas de asignación de recursos que no estén basadas en la ruta crítica sino en la información de recursos y de la estructura de la red.es_CO
dc.language.isospaes_CO
dc.publisherUniversidad de La Sabana
dc.sourceUniversidad de La Sabana
dc.sourceIntellectum Repositorio Universidad de La Sabana
dc.titleAnálisis de la relación entre políticas de asignación de recursos en la atención de desastres y la mortalidades_CO
dc.typemasterThesis
dc.publisher.programMaestría en Diseño y Gestión de Procesos
dc.publisher.departmentFacultad de Ingeniería
dc.identifier.local258842
dc.identifier.localTE06326
dc.type.localTesis de maestría
dc.type.hasVersionpublishedVersion
dc.rights.accessRightsopenAccess
dc.creator.degreeMagíster en Diseño y Gestión de Procesos


Ficheros en el ítem

Thumbnail
Nombre:
María Catalina González Forero ...
Tamaño:
5.852Mb
Formato:
PDF
Descripción:
Ver documento en PDF
Ver/

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem