Análisis de la asignación de recursos asociados a las actividades repetitivas en la ejecución de proyectos en una organización por proyectos

dc.contributor.advisorRocha González, Jair Eduardospa
dc.contributor.authorSanabria Rodríguez, Nicolásspa
dc.date.accessioned2020-12-14T16:52:26Zspa
dc.date.available2020-12-14T16:52:26Zspa
dc.date.issued2020-08-19spa
dc.description.abstractLas empresas colombianas necesitan metodologías para poder mejorar su competitividad, para lo cual es necesario optimizar el uso de recursos y la planeación de actividades en las empresas. Con este fin, se decidió aplicar la técnica de la curva de aprendizaje para tener un mejor control sobre la duración de las actividades, pero no en empresas de manufactura dónde el tema ya ha sido estudiado ampliamente sino en empresas que trabajan por proyectos y que repiten algunas actividades varias veces. Se eligió una fundación sin ánimo de lucro especializada en la enseñanza de metodologías de liderazgo a jóvenes de escasos recursos, y cinco actividades asociadas repetidas a lo largo de 12 proyectos y 7 años, y se recolectaron datos de duración, personal y costo presupuestado de las actividades. Luego de procesar los datos se realizaron regresiones lineales y curvilíneas para encontrar las variables de mayor peso en la duración de la actividad, las cuales fueron principalmente la experiencia acumulada a través del tiempo, y el número de personas en algunos casos. Los datos del rendimiento del equipo también se compararon con los resultados de la curva Stanford B de Yelle (1979), pero los modelos no resultaron tan precisos como los obtenidos a través de regresiones lineales. Aunque los modelos no tienen un ajuste preciso, se concluye que es posible aplicar los conceptos de curva de aprendizaje en industrias no manufactureras y con enfoque social (Texto tomado de la fuente).spa
dc.description.abstractColombian companies need ways to improve their competitiveness, with that objective in mind they need to optimize their use of resources as well as their activity scheduling. With this in mind, the learning curve technique was used in order to have better control over the activity duration, but not in manufacturing companies where the topic has been widely studied but in companies that work by projects which have activities repeated numerous times. A nonprofit organization specialized on the teaching of leadership techniques was chosen, along with five associated activities repeated throughout 12 projects and 7 years, and activity duration, personnel and cost data were collected. After processing the data, lineal and curvilinear regressions were made in order to find the variables with the most weight on the activity duration, those being the experience accumulated through time as well as the number of people and the project type in some cases. Team performance data were also compared with the Stanford B model by Yelle (1979) and both results were similar, however, models did not result as precise as the ones obtained through linear regressions. Even though the regression models did not have an accurate adjustment, it can be concluded that it is possible to apply the learning curve models in non-manufacturing industries with social scope.spa
dc.description.degreelevelMaestríaspa
dc.description.researchareaOperaciones y productividadspa
dc.format.extent143 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/78708
dc.language.isospaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.programBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería Industrialspa
dc.relation.referencesArias Gaviria, J. (2014). Modelamiento y simulación de curvas de aprendizaje para tecnologías de energía renovable en Colombia. Universidad Nacional de Colombia - Sede Medellín.spa
dc.relation.referencesAnzanello, M. J., & Fogliatto, F. S. (2011). Learning curve models and applications: Literature review and research directions. International Journal of Industrial Ergonomics.spa
dc.relation.referencesDeJong, J.R. (1957) The Effects of Increasing Skill on Cycle Time And Its Consequences For Time Standards. Ergonomics 1, 1, 51-60.spa
dc.relation.referencesEden, C. (2004); Dismantling the learning curve: The role of disruptions on the planning of development projects. Department of Management Science, University of Strathclyde, 40 George Street, United Kingdom.spa
dc.relation.referencesFeriyanto, N., Saleh, C., Badri, H. M., Md Deros, B., & Pratama, Y. (2015). Implementation learning and forgetting curve to predict needs and decrease of laborse performance after break. Jurnal Teknologi, 77(27).spa
dc.relation.referencesJarkas, A. M. (2010). Critical Investigation into the Applicability of the Learning Curve Theory to Rebar Fixing Labor Productivity. Journal of Construction Engineering and Management, 136(12), 1279–1288.spa
dc.relation.referencesMályusz, L., & Varga, A. (2017). An Estimation of the Learning Curve Effect on Project Scheduling with Calendar Days Calculation. In Procedia Engineering (Vol. 196, pp. 730–737).spa
dc.relation.referencesWright, T. (1936). "Factors Affecting the Cost of Airplanes", Journal of the Aeronautical Sciences, Vol. 3, No. 4 (1936), pp. 122-128.spa
dc.relation.referencesAcosta, W. (2001) Redes y PERT/CPM, método del camino crítico. Gestiopolis. Recuperado el 27 de agosto de 2018 en https://www.gestiopolis.com/redes-y-pert-cpm-metodo-del-camino-critico/spa
dc.relation.referencesAdler, P. & Clark, K. (1991). Behind the Learning Curve: A Sketch of the Learning Process. Management Science 37, 267-281.spa
dc.relation.referencesAhmadian Fard Fini, A., Rashidi, T. H., Akbarnezhad, A., & Travis Waller, S. (2016). Incorporating Multiskilling and Learning in the Optimization of Crew Composition. Journal of Construction Engineering and Management, 142(5), 04015106.spa
dc.relation.referencesAhmadizar, F., & Hosseini, L. (2012). Bi-criteria single machine scheduling with a time-dependent learning effect and release times. Applied Mathematical Modelling, 36(12), 6203–6214.spa
dc.relation.referencesAmmar, M. & Abdel-Maged, A. (2017). Modeling of LOB scheduling with learning development effect. International Journal of Construction Management.spa
dc.relation.referencesAn, S., Ji, S., Hyun, C. & Han, S. (2015) A model-based productivity improvement of reinforced concrete work in a multi-housing project. KSCE Journal of Civil Engineering 19, 5, 1183-1192.spa
dc.relation.referencesAnzanello, M. Fogliatto, F. S. (2007). Learning curve modelling of work assignment in mass customized assembly lines. International Journal of Production Research, 45, 13, 2919-2938.spa
dc.relation.referencesAnzanello, M. J. Fogliatto, F. S. (2010). Scheduling learning dependent jobs in customized assembly lines. International Journal of Production Research, 48,22, 6683-6699.spa
dc.relation.referencesBabu, A.& Suresh, N. (1996) Project management with time, cost, and quality considerations. European Journal of Operational Research 88, 2, 320-327.spa
dc.relation.referencesBadiru, A. B. (1992). Computational Survey of Univariate and Multivariate Learning Curve Models. IEEE Transactions on Engineering Management, 39(2), 176–188.spa
dc.relation.referencesBadiru, A. Ijaduola (2009). A. Half-Life Theory of Learning Curves for System Performance Analysis. IEEE Systems Journal, 2, 164-165.spa
dc.relation.referencesBailey, C.D. & Mcyntre (1997) The relation between fit and prediction for alternative forms of learning curves and relearning curves. E.V. IIE Transactions 29: 487.spa
dc.relation.referencesBaloff,N. (2017) Extension of the Learning Curve — Some Empirical Results, Journal of the Operational Research Society, 22:4, 329-340.spa
dc.relation.referencesBassett, M. (2000). Assigning projects to optimize the utilization of employees’ time and expertise. In Computers and Chemical Engineering (Vol. 24, pp. 1013–1021).spa
dc.relation.referencesBecerra, L. (2018) Productividad de las empresas, afectada por la ineficiencia. Recuperado el 20 de agosto de 2018 en https://www.eltiempo.com/economia/empresas/productividad-en-empresas-colombianas-238874spa
dc.relation.referencesBiskup, D. (2008). A state-of-the-art review on scheduling with learning effects. European Journal of Operational Research, 188(2), 315–329.spa
dc.relation.referencesBlancett, R. (2016) Learning from Productivity Learning Curves, Research-Technology Management,45:3, 54-58.spa
dc.relation.referencesBlanning, R. (1981). Variable-base budgeting for R&D. Management Science 27 (5), 547-558.spa
dc.relation.referencesBowman, R. (2006). Developing activity duration specification limits for effective project control. European Journal of Operational Research, 2, 1191-1204.spa
dc.relation.referencesChambers S., & Johnston, R. (2000) Experience curves in services: macro and micro level approaches. International Journal of Operations & Production Management 20 (7), 842-859.spa
dc.relation.referencesCheng, M. (2013). Flowshop scheduling problems with a position-dependent exponential learning effect. Mathematical Problems in Engineering, 2013.spa
dc.relation.referencesConsejo Privado de Competitividad (2018). ¿Por qué un pacto por la productividad? Recuperado el 20 de agosto de 2018 en https://compite.com.co/por-que-un-pacto-por-la-productividad/spa
dc.relation.referencesCook, J. (1991) A competitive model of the Japanese firm. Journal of Policy ModelingVolume 13, Issue 1, Spring 1991, 93-114.spa
dc.relation.referencesCook, S. (1971) The complexity of theorem proving procedures. Proceedings of the 3rd annual ACM Symposium on theory of computing., 151-158.spa
dc.relation.referencesEden C., Willians, T. & Ackermann F. (1998). Dismantling the learning curve; the role of disruptions on the planning of development projects. International Journal of Project Management 16 (3), 131-138.spa
dc.relation.referencesEden, C. (2004); Dismantling the learning curve: The role of disruptions on the planning of development projects. Department of Management Science, University of Strathclyde, 40 George Street, United Kingdom.spa
dc.relation.referencesEllis Jr., R. & Lee, S. (2006) Measuring project level productivity on transportation projects. Journal of Construction Engineering and Management 132, 3, 314-320.spa
dc.relation.referencesElmaghraby, S.E. (1993) Resource allocation via dynamic programming in activity networks. European Journal of Operational Research 64, 2, 199-215.spa
dc.relation.referencesEmmons, H. (1969) One-machine sequence to minimize certain functions of job tardiness. Ergun, H.& Pradhananga, N. (2015) Real-time location data for automated learning curve analysis of linear repetitive construction activities. Congress on Computing in Civil Engineering, Proceedings, 107-114spa
dc.relation.referencesEverett, J. G., & Farghal, S. H. (1997). Data Representation for Predicting Performance with Learning Curves. Journal of Construction Engineering and Management, 123(1), 46–52.spa
dc.relation.referencesFarghal, S., Everett, J. (1997) Learning Curves: Accuracy in Predicting Future Performance. Journal of Construction Engineering and Management 123,1-45.spa
dc.relation.referencesFedorowicz, J., Oz, E., & Berger, P. D. (1992). A Learning Curve Analysis of Expert System Use. Decision Sciences, 23(4), 797–818.spa
dc.relation.referencesFeriyanto, N., Saleh, C., Badri, H. M., Md Deros, B., & Pratama, Y. (2015). Implementation learning and forgetting curve to predict needs and decrease of laborse performance after break. Jurnal Teknologi, 77(27).spa
dc.relation.referencesFine, C. H. (1986). Quality Improvement and Learning in Productive Systems. Management Science, 32(10), 1301–1315.spa
dc.relation.referencesFioretti, G. (2007). The organizational learning curve. European Journal of Operational Research, 177(3), 1375–1384.spa
dc.relation.referencesG Wang, J. B., & Wang, C. (2011). Single-machine due-window assignment problem with learning effect and deteriorating jobs. Applied Mathematical Modelling, 35(8), 4017–4022.spa
dc.relation.referencesGivi, Z. S., Jaber, M. Y., & Neumann, W. P. (2015). Production planning in DRC systems considering worker performance. Computers and Industrial Engineering, 87, 317–327.spa
dc.relation.referencesGloberson, S. (1984). The deviation of actual performance around learning curve models. International Journal of Production Research, 22(1), 51–62.spa
dc.relation.referencesGloberson, S. (1989) The deviation of actual performance around learning curve models,International Journal of Production Research, 22:1, 51-62.spa
dc.relation.referencesGloberson, S., & Gold, D. (1997). Statistical attributes of the power learning curve model. International Journal of Production Research, 35(3), 699–711.spa
dc.relation.referencesGraham, R., Lawler, E., Lenstra, J. & Rinnoy, K. (1979). Optimization and approximiation in deterministic sequencing and scheduling. A survey. Annals of Discrete Mathemathics 5: 287-326.spa
dc.relation.referencesGrosse, E. Glock, C.Müller, S. (2015). Production economics and the learning curve: A meta-analysis. International Journal of Production Economics, 170, 401-412.spa
dc.relation.referencesGruber, H. (1992). The learning curve in the production of semiconductor memory chips. Applied Economics, 24(8), 885–894.spa
dc.relation.referencesGruber, H. (1994). The yield factor and the learning curve in semiconductor production. Applied Economics, 26(8), 837–843.spa
dc.relation.referencesHardie, N. (2001). The prediction and control of project duration: A recursive model. International Journal of Project Management, 19(7), 401–409.spa
dc.relation.referencesHartley, K (1965). The Learning Curve and Its Application to the Aircraft Industry. The Journal of Industrial Economics, 2, 122-128.spa
dc.relation.referencesHartmann, S., & Briskorn, D. (2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of Operational Research.spa
dc.relation.referencesHeideger, K., & Stummer, C. (1999) Research and development project selection and resource allocation:a review of quantitative modelling approaches. International Journal of Management Reviews 1,2, 197-224.spa
dc.relation.referencesHelin A., Soulder, W. (1974). Experimental test of a Q-sort procedure for prioritizing R&D projects. IEEE Transactions on Engineering Management, 21(4) 159-164.spa
dc.relation.referencesHernandez Sampieri, R., Fernández Collado, C. & Baptista Lucio, M. (2014) Metodología de la investigación, sexta edición. Ciudad de México, México. Ed. Mc Graw Hill.spa
dc.relation.referencesHijazi, A., Abourizk, S. & Halpin, D. (1992) Modeling and simulating learning development in construction. Journal of Construction Engineering and Management 118, 4, 685-700.spa
dc.relation.referencesHorenburg, T. & Günthner, W. (2013) Construction scheduling and resource allocation based on actual state data. Computing in Civil Engineering - Proceedings of the 2013 ASCE International Workshop on Computing in Civil Engineering, Pages 741-748.spa
dc.relation.referencesHowick, S. & Eden, C. (2007) Learning in disrupted projects: on the nature of corporate and personal learning, International Journal of Production Research, 45:12, 2775-2797.spa
dc.relation.referencesJ.W. Hurley (1996) When are we going to change the learning curve lecture? Computers Operations Research, 23 (5) (1996), pp. 509-511.spa
dc.relation.referencesJaber, M. Y., & Glock, C. H. (2013). A learning curve for tasks with cognitive and motor elements. Computers and Industrial Engineering, 64(3), 866–871.spa
dc.relation.referencesJaber, M.Y. &Guiffrida, A.L. (2004) Learning curves for processes generating defects requiring reworks. European Journal of Operational Research 159, 3, 663-672.spa
dc.relation.referencesJaber, M.Y., Bonney, M. (2007) Economic manufacture quantity (EMQ) model with lot-size dependent learning and forgetting rates. International Journal of Production Economics Volume 108, 1-2,359-367spa
dc.relation.referencesJaber, M.Y., Khan, M. (2007) Managing yield by lot splitting in a serial production line with learning, rework and scrap. International Journal of Production Economics 124, 1, 32-39.spa
dc.relation.referencesJackson, B. (1983a) Decision models for evaluating R&D projects. Research Management 26(4), 16-22.spa
dc.relation.referencesJackson, B. (1983b) Decision models for selecting a portfolio of R&D projects. Research Management 26(5), 21-26.spa
dc.relation.referencesJarkas, A. M. (2010). Critical Investigation into the Applicability of the Learning Curve Theory to Rebar Fixing Labor Productivity. Journal of Construction Engineering and Management, 136(12), 1279–1288.spa
dc.relation.referencesJarkas, A., & Horner, M. (2011). Revisiting the applicability of learning curve theory to formwork labour productivity. Construction Management and Economics, 29(5), 483–493.spa
dc.relation.referencesJoshi, D. (2019) A Teaching–Learning-Based Optimization Algorithm for the Resource-Constrained Project Scheduling Problem. Harmony Search and Nature Inspired Optimization Algorithms, Advances in Intelligent Systems and Computing 741, 1101-1109spa
dc.relation.referencesKalenatic, D. (1987) Técnicas de Planeación de Redes. Bogotá, Colombia. Ed. Universidad Distrital Francisco José de Caldas.spa
dc.relation.referencesKher, H. V., Malhotra, M. K., Philipoom, P. R., & Fry, T. D. (1999). Modeling simultaneous worker learning and forgetting in dual resource constrained systems.spa
dc.relation.referencesKoltai, T., & Kalló, N. (2017). Analysis of the effect of learning on the throughput-time in simple assembly lines. Computers and Industrial Engineering, 111, 507–515.spa
dc.relation.referencesKunal, K., Pandey, & Maheswari, J. (2016) Rationalizing Project Schedules Using Realistic Baseline Worker Productivity. Construction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan.spa
dc.relation.referencesKuo, W. H., Hsu, C. J., & Yang, D. L. (2012). Worst-case and numerical analysis of heuristic algorithms for flowshop scheduling problems with a time-dependent learning effect.spa
dc.relation.referencesLam, K. C., Lee, D., & Hu, T. (2001). Understanding the effect of the learning-forgetting phenomenon to duration of projects construction. International Journal of Project Management, 19(7), 411–420.spa
dc.relation.referencesLee, B., Lee, H., Park, M., & Kim, H. (2015). Influence Factors of Learning-Curve Effect in High-Rise Building Constructions. Journal of Construction Engineering and Management, 141(8), 1–11.spa
dc.relation.referencesLi, G. & Rajagopalan, S. (1998) A learning curve model with knowledge depreciation. European Journal of Operational Research 105 (1), 143-154.spa
dc.relation.referencesLi, H., & Womer, K. (2009). Scheduling projects with multi-skilled personnel by a hybrid MILP/CP benders decomposition algorithm. Journal of Scheduling, 12(3), 281–298.spa
dc.relation.referencesLin, C., Huang, M. (2008) Model for measuring baseline productivity - A case study of structural steel erection. Journal of the Chinese Institute of Civil and Hydraulic Engineering 20, 2, 257-268.spa
dc.relation.referencesLuh, Y. Stefanou, E. (1993). Learning-by-doing and the sources of productivity growth: A dynamic model with application to U.S. agriculture. Journal of Productivity Analysis, 4, 4, 353-370.spa
dc.relation.referencesMacher, J. T., & Mowery, D. C. (2003). “Managing” Learning by Doing: An Empirical Study in Semiconductor Manufacturing. Journal of Product Innovation Management, 20(5), 391–410.spa
dc.relation.referencesMahjoubpour, B., Nasirzadeh, F. Golabchi, M. Khajehghiasi, M. & Mir, M. (2018) Modeling of workers’ learning behavior in construction projects using agent-based approach: The case study of a steel structure project. Engineering, Construction and Architectural Management 25, 4, 559-573spa
dc.relation.referencesMalyusz, L., & Pem, A. (2014). Predicting Future Performance by Learning Curves. Procedia - Social and Behavioral Sciences, 119, 368–376.spa
dc.relation.referencesMaravas, A. & Pantouvakis, J. (2009) Fuzzy repetitive scheduling method for projects with repeating activities. Journal of Construction Engineering and Management 137, 7, 561-564 Mazur, J. & Hastle, R. (1978) Learning as accumulation: a reexamination of the learning curve. Psychological bulletin 85 (6), 1256-1274.spa
dc.relation.referencesMcNaughton, R. (1959) Scheduling with deadlines and loss functions. Management Science 6, 1-12.spa
dc.relation.referencesMiranda Miranda, J. (2005). Gestión de proyectos. Bogotá, Colombia. Editorial MM.spa
dc.relation.referencesNabeshima (1967) On the bound of makespans and its application in M machine scheduling problem. Journal of the Operations Research Society in Japan 9: 98-136.spa
dc.relation.referencesNembhard, D., Uzumeri, M. (2000a). An individual-based description of learning whitin an organization. IEEE Transactions on Engineering Management 47 (3), 370-378.spa
dc.relation.referencesNembhard, D., Uzumeri, M. (2000b). Experimental learning and forgetting for manual and cognitive tasks. International Journal of Industrial Ergonomics 25 (3), 315-326.spa
dc.relation.referencesNg, S.T. & Zhang, Y. (2008) Optimizing construction time and cost using ant colony optimization approach. Journal of Construction Engineering and Management 134, 9, 721-728spa
dc.relation.referencesNgwenyama, O., Guergachi, A., & McLaren, T. (2007). Using the learning curve to maximize IT productivity: A decision analysis model for timing software upgrades. International Journal of Production Economics, 105(2), 524–535.spa
dc.relation.referencesNiño, E., Ardila, C., Perez, A., & Donoso, Y. (2010). A Genetic Algorithm for Multiobjective Hard Scheduling Optimization. International Journal of Computers Communications & Control (2010) 5(5) 825-836.spa
dc.relation.referencesONU (1958). Manual de proyectos de desarrollo económico. México D.F., Naciones Unidas.spa
dc.relation.referencesPanas, A., & Pantouvakis, J. (2017) On the use of learning curves for the estimation of construction productivity. International Journal of Construction Management 18-4, 301-309.spa
dc.relation.referencesPanwalkar, S. S.,Iskander, W (1977). A Survey of Scheduling Rules. Operations Research. Paolini, A. & Glaser, M. (1977). Project selection methods that bring winners. Research Management 20(3), 26-29.spa
dc.relation.referencesPérez Uribe, R. & Ortiz Rojas, W. (2010) Efectos de la gestión organizacional en la rentabilidad en pymes: Evidencias empíricas y algunas consideraciones teóricas. Revista Escuela Administración de Negocios. n.69, 88-109.spa
dc.relation.referencesPlaza, M.& Rohlf, K. (2008) Learning and performance in ERP implementation projects: A learning-curve model for analyzing and managing consulting costs. International Journal of Production Economics 115, 1, 72-85spa
dc.relation.referencesPotts, C. N., Strusevich, V. A. (2009). Fifty years of scheduling: A survey of milestones. Journal of the Operational Research Society.spa
dc.relation.referencesPrieto Herrera, J. (2004). Proyectos: Enfoque gerencial. Bogotá, Colombia. Ecoe Ediciones.spa
dc.relation.referencesProject Management Institute (2013) Guía de los fundamentos para la dirección de proyectos. Project Management Institute Inc.spa
dc.relation.referencesRodríguez Devis, J. (2000). La gerencia sistémica de proyectos de investigación en Ingeniería. Bogotá, Colombia. Editorial Universidad Nacional de Colombia.spa
dc.relation.referencesRudek, R. (2012). The single processor total weighted completion time scheduling problem with the sum-of-processing-time based learning model.spa
dc.relation.referencesSaaty, T. (1980) The Analytical Hierarchy Process. New York: Mc Graw Hill. Sallenave, J. (1985) Gerencia y planeación estratégica. Editorial Norma.spa
dc.relation.referencesSenouci, A., & El-Rayes, K. (2009) Time-Profit Trade-Off Analysis for Construction Projects. Journal of Construction Engineering and Management 135, 8spa
dc.relation.referencesShee, A. Stefanou, E. (2016). Bounded learning-by-doing and sources of firm level productivity growth in colombian food manufacturing industry. Journal of Productivity Analysis 46, 2-3, 185-197.spa
dc.relation.referencesStorer, R., Wu S., & Vaccari, R. (1992) New search spaces for sequencing problems with application to job shop scheduling. Management Science 38:1945-1509.spa
dc.relation.referencesSusan Howick & Colin Eden (2007) Learning in disrupted projects: on the nature of corporate and personal learning, International Journal of Production Research, 45:12, 2775-2797.spa
dc.relation.referencesTilindis, J. & Kleiza, V. (2017) Learning curve parameter estimation beyond traditional statistics. Applied Mathematical Modelling 45: 768-783spa
dc.relation.referencesToro López, F. (2011) Gestión de proyectos con enfoque PMI al usar Project y Excel. Bogotá, Colombia. Ecoe Ediciones.spa
dc.relation.referencesTran, D., Luong-Duc, L., Duong, M., Le, T. & Pham, A. (2018) Opposition multiple objective symbiotic organisms search (OMOSOS) for time, cost, quality and work continuity tradeoff in repetitive projects. Journal of Computational Design and Engineering 5, 2, 160-172spa
dc.relation.referencesTsai, H., Moskowitz, H., Lee, L. (2003) Human resource selection for software development projects using Taguchi's parameter design. European Journal of Operational Research 151, 1, 167-180spa
dc.relation.referencesVan Peteghem, V., & Vanhoucke, M. (2015). Influence of learning in resource-constrained project scheduling. Computers and Industrial Engineering, 87, 569–579.spa
dc.relation.referencesVargas-Nieto, F. Montoya-Torres, J. (2007). Scheduling a thermal-printed label manufacturing plant using an evolutionary algorithm. 19th International Conference on Production Researchspa
dc.relation.referencesVenkatesh, M., Renuka, S., Malathi, B. & Umarani, C. (2012) Evaluation of critical factors influencing resource allocation in Indian construction projects. Applied Mechanics and Materials 174-177, 2774-2777spa
dc.relation.referencesWickramasinghe, V. & Gunawardena, V. (2010) Effects of people-centred factors on enterprise resource planning implementation project success: Empirical evidence from Sri Lanka. Enterprise Information Systems 4, 3, 311-328spa
dc.relation.referencesWiersma, E (2007). Conditions That Shape the Learning Curve: Factors That Increase the Ability and Opportunity to Learn, Management Science.spa
dc.relation.referencesWong, P. S. P., On Cheung, S., & Hardcastle, C. (2007). Embodying Learning Effect in Performance Prediction. Não Texto, 133(6), 474–482spa
dc.relation.referencesWu, M.-C., & Sun, S.-H. (2006). A project scheduling and staff assignment model considering learning effect. The International Journal of Advanced Manufacturing Technology, 28(11–12), 1190–1195.spa
dc.relation.referencesYelle, L.E. (1979) The learning curve: historical review and comprehensive survey. Decis. Sci.,10, 302-328spa
dc.relation.referencesZha, H., & Zhang, L. (2014). Scheduling projects with multiskill learning effect. The Scientific World Journal, 2014.spa
dc.relation.referencesZhang, X., Sun, L., & Wang, J. (2013). Single machine scheduling with autonomous learning and induced learning. Computers and Industrial Engineering, 66(4), 918–924.spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacionalspa
dc.rights.spaAcceso abiertospa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.ddc650 - Gerencia y servicios auxiliares::658 - Gerencia generalspa
dc.subject.proposalLearning curveeng
dc.subject.proposalCurva de aprendizajespa
dc.subject.proposalActividades repetitivasspa
dc.subject.proposalRepetitive activitieseng
dc.subject.proposalProject resourceseng
dc.subject.proposalRecursos en proyectosspa
dc.subject.proposalCompetitividadspa
dc.subject.proposalCompetitivenesseng
dc.subject.proposalProductivityeng
dc.subject.proposalProductividadspa
dc.titleAnálisis de la asignación de recursos asociados a las actividades repetitivas en la ejecución de proyectos en una organización por proyectosspa
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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Tesis de Maestría en Ingeniería - Industrial

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