Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta
diagramas, ilustraciones a color, mapas, tablas
- Autores:
-
López Castillo, Iván Darío
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/79577
- Palabra clave:
- 620 - Ingeniería y operaciones afines
Logística
Logistics
Canales de distribución
Distribution channels
Diseño de cadena de suministro
Centros de abastecimiento y distribución
Modo de transporte
Tiempos de entrega
Costos logísticos
Supply Chain Network Design
SCND
Distribution Centers
Mode of transport
Lead time
Logistics Costs
- Rights
- openAccess
- License
- Reconocimiento 4.0 Internacional
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| dc.title.spa.fl_str_mv |
Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta |
| dc.title.translated.eng.fl_str_mv |
Proposal for the configuration of a logistics network of pharmaceutical products under the criteria of costs and response times |
| title |
Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta |
| spellingShingle |
Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta 620 - Ingeniería y operaciones afines Logística Logistics Canales de distribución Distribution channels Diseño de cadena de suministro Centros de abastecimiento y distribución Modo de transporte Tiempos de entrega Costos logísticos Supply Chain Network Design SCND Distribution Centers Mode of transport Lead time Logistics Costs |
| title_short |
Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta |
| title_full |
Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta |
| title_fullStr |
Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta |
| title_full_unstemmed |
Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta |
| title_sort |
Propuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuesta |
| dc.creator.fl_str_mv |
López Castillo, Iván Darío |
| dc.contributor.advisor.none.fl_str_mv |
Castrellón Torres, Juan Pablo |
| dc.contributor.author.none.fl_str_mv |
López Castillo, Iván Darío |
| dc.contributor.researchgroup.spa.fl_str_mv |
Grupo de investigación de operaciones de la Universidad Nacional de Colombia: UNGIDO |
| dc.subject.ddc.spa.fl_str_mv |
620 - Ingeniería y operaciones afines |
| topic |
620 - Ingeniería y operaciones afines Logística Logistics Canales de distribución Distribution channels Diseño de cadena de suministro Centros de abastecimiento y distribución Modo de transporte Tiempos de entrega Costos logísticos Supply Chain Network Design SCND Distribution Centers Mode of transport Lead time Logistics Costs |
| dc.subject.other.none.fl_str_mv |
Logística Logistics Canales de distribución Distribution channels |
| dc.subject.proposal.spa.fl_str_mv |
Diseño de cadena de suministro Centros de abastecimiento y distribución Modo de transporte Tiempos de entrega Costos logísticos |
| dc.subject.proposal.eng.fl_str_mv |
Supply Chain Network Design SCND Distribution Centers Mode of transport Lead time Logistics Costs |
| description |
diagramas, ilustraciones a color, mapas, tablas |
| publishDate |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2021-05-31T19:55:04Z |
| dc.date.available.none.fl_str_mv |
2021-05-31T19:55:04Z |
| dc.date.issued.none.fl_str_mv |
2021-04 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
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info:eu-repo/semantics/masterThesis |
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info:eu-repo/semantics/acceptedVersion |
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Text |
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http://purl.org/redcol/resource_type/TM |
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acceptedVersion |
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https://repositorio.unal.edu.co/handle/unal/79577 |
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Universidad Nacional de Colombia |
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Repositorio Institucional Universidad Nacional de Colombia |
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https://repositorio.unal.edu.co/ |
| url |
https://repositorio.unal.edu.co/handle/unal/79577 https://repositorio.unal.edu.co/ |
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Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
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spa |
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spa |
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Alzaman, C., Zhang, Z. H., & Diabat, A. (2018). Supply chain network design with direct and indirect production costs: Hybrid gradient and local search based heuristics. International Journal of Production Economics, 203(May), 203–215. https://doi.org/10.1016/j.ijpe.2018.06.004 Ambrosino, D., & Grazia Scutellà, M. (2005). Distribution network design: New problems and related models. European Journal of Operational Research, 165(3), 610–624. https://doi.org/10.1016/j.ejor.2003.04.009 BALLOU. (2004). BALLOU. Logística. Administración de la Cadena de Suministro (1).pdf. Bernal, C. A. (2016). Metodología de la investigación (T. Edicion (ed.); Vol. 4, Issue 1). Biuki, M., Kazemi, A., & Alinezhad, A. (2020). An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network. Journal of Cleaner Production, 260, 120842. https://doi.org/10.1016/j.jclepro.2020.120842 Castrillón R, M. L. (2018). Análisis Sector Farmacéutico. Estudios Sobre La Bioeconomía Como Fuente de Nuevas Industrias Basadas En El Capital Natural de Colombia, 30. https://www.dnp.gov.co/Crecimiento-Verde/Documents/ejes-tematicos/Bioeconomia/Informe 2/ANEXO 5_Análisis sector farmaceutico.pdf Chatzikontidou, A., Longinidis, P., Tsiakis, P., & Georgiadis, M. C. (2017). Flexible supply chain network design under uncertainty. Chemical Engineering Research and Design, 128, 290–305. https://doi.org/10.1016/j.cherd.2017.10.013 Chopra, S. (2003). Designing the distribution network in a supply chain. 39, 123–140. Coelho, L. C., & Laporte, G. (2014). Optimal joint replenishment, delivery and inventory management policies for perishable products. Computers and Operations Research, 47, 42–52. https://doi.org/10.1016/j.cor.2014.01.013 Creswell, J. W. (2008). RESEARCH DESIGN: Qualitative, Quantitative, and Mixed Methods Approaches (Third Edit). Darestani, S. A., & Hemmati, M. (2019). Robust optimization of a bi-objective closed-loop supply chain network for perishable goods considering queue system. Computers and Industrial Engineering, 136(February), 277–292. https://doi.org/10.1016/j.cie.2019.07.018 EMIS. (2020). Industry Report Healthcare Colombia. Emis, A., & Industry, I. (2020). COLOMBIA PHARMA & HEALTHCARE SECTOR 2020/2021. Farahani, R. Z., Rezapour, S., Drezner, T., & Fallah, S. (2014). Competitive supply chain network design: An overview of classifications, models, solution techniques and applications. Omega (United Kingdom), 45, 92–118. https://doi.org/10.1016/j.omega.2013.08.006 FINCA RAIZ. (2020). https://www.fincaraiz.com.co/. https://www.fincaraiz.com.co/ Gen, M., Lin, L., Yun, Y. S., & Inoue, H. (2018). Recent advances in hybrid priority-based genetic algorithms for logistics and SCM network design. Computers and Industrial Engineering, 125(September), 394–412. https://doi.org/10.1016/j.cie.2018.08.025 Ghaderi, H., Pishvaee, M. S., & Moini, A. (2016). Biomass supply chain network design: An optimization-oriented review and analysis. Industrial Crops and Products, 94, 972–1000. https://doi.org/10.1016/j.indcrop.2016.09.027 Goodarzian, F., Hosseini-Nasab, H., Muñuzuri, J., & Fakhrzad, M. B. (2020). A multi-objective pharmaceutical supply chain network based on a robust fuzzy model: A comparison of meta-heuristics. Applied Soft Computing Journal, 92, 106331. https://doi.org/10.1016/j.asoc.2020.106331 Govindan, K., Jafarian, A., Khodaverdi, R., & Devika, K. (2014). Two-echelon multiple-vehicle location-routing problem with time windows for optimization of sustainable supply chain network of perishable food. International Journal of Production Economics, 152, 9–28. https://doi.org/10.1016/j.ijpe.2013.12.028 Govindan, Kannan, Jafarian, A., & Nourbakhsh, V. (2015). Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic. Computers and Operations Research, 62, 112–130. https://doi.org/10.1016/j.cor.2014.12.014 Guillén, G., Mele, F. D., Bagajewicz, M. J., Espuña, A., & Puigjaner, L. (2005). Multiobjective supply chain design under uncertainty. Chemical Engineering Science, 60(6), 1535–1553. https://doi.org/10.1016/j.ces.2004.10.023 Hansen, K. R. N., & Grunow, M. (2015). Planning operations before market launch for balancing time-to-market and risks in pharmaceutical supply chains. International Journal of Production Economics, 161, 129–139. https://doi.org/10.1016/j.ijpe.2014.10.010 Hinojosa, Y., Kalcsics, J., Nickel, S., Puerto, J., & Velten, S. (2008). Dynamic supply chain design with inventory. Computers and Operations Research, 35(2), 373–391. https://doi.org/10.1016/j.cor.2006.03.017 Hugo, A., & Pistikopoulos, E. N. (2005). Environmentally conscious long-range planning and design of supply chain networks. Journal of Cleaner Production, 13(15), 1428–1448. https://doi.org/10.1016/j.jclepro.2005.04.011 INVIMA (Instituto de Vigilancia de Medicamentos y alimentos). (2018). Informe de gestión del desabastecimiento de medicamentos en Colombia 2013-2018. 1–4. https://www.invima.gov.co/desabastecimiento- Jang, Y. J., Jang, S. Y., Chang, B. M., & Park, J. (2002). A combined model of network design and production/distribution planning for a supply network. Computers & Industrial Engineering, 43, 263–281. https://doi.org/Pii S0360-8352(02)00074-8\nDoi 10.1016/S0360-8352(02)00074-8 Jouzdani, J., & Govindan, K. (2020). On the sustainable perishable food supply chain network design: A dairy products case to achieve sustainable development goals. Journal of Cleaner Production, 278, 123060. https://doi.org/10.1016/j.jclepro.2020.123060 Kelle, P., Woosley, J., & Schneider, H. (2012). Pharmaceutical supply chain specifics and inventory solutions for a hospital case. Operations Research for Health Care, 1(2–3), 54–63. https://doi.org/10.1016/j.orhc.2012.07.001 Klibi, W., & Martel, A. (2012). Scenario-based Supply Chain Network risk modeling. European Journal of Operational Research, 223(3), 644–658. https://doi.org/10.1016/j.ejor.2012.06.027 Lemmens, S., Decouttere, C., Vandaele, N., & Bernuzzi, M. (2016). A review of integrated supply chain network design models: Key issues for vaccine supply chains. Chemical Engineering Research and Design, 109, 366–384. https://doi.org/10.1016/j.cherd.2016.02.015 Lieckens, K., & Vandaele, N. (2007). Reverse logistics network design with stochastic lead times. Computers and Operations Research, 34(2), 395–416. https://doi.org/10.1016/j.cor.2005.03.006 Lowe, T. J., Wendell, R. E., & Hu, G. (2002). Screening location strategies to reduce exchange rate risk. European Journal of Operational Research, 136(3), 573–590. https://doi.org/10.1016/S0377-2217(01)00065-0 Luo, H., Yang, X., & Wang, K. (2019). Synchronized scheduling of make to order plant and cross-docking warehouse. Computers and Industrial Engineering, 138(October), 106108. https://doi.org/10.1016/j.cie.2019.106108 Martins, S., Amorim, P., Figueira, G., & Almada-Lobo, B. (2017). An optimization-simulation approach to the network redesign problem of pharmaceutical wholesalers. Computers and Industrial Engineering, 106, 315–328. https://doi.org/10.1016/j.cie.2017.01.026 Masoumi, A. H., Yu, M., & Nagurney, A. (2012). A supply chain generalized network oligopoly model for pharmaceuticals under brand differentiation and perishability. Transportation Research Part E: Logistics and Transportation Review, 48(4), 762–780. https://doi.org/10.1016/j.tre.2012.01.001 Meixell, M. J., & Gargeya, V. B. (2005). Global supply chain design: A literature review and critique. Transportation Research Part E: Logistics and Transportation Review, 41(6 SPEC. ISS.), 531–550. https://doi.org/10.1016/j.tre.2005.06.003 Melo, M. T., Nickel, S., & Saldanha-da-Gama, F. (2009). Facility location and supply chain management - A review. European Journal of Operational Research, 196(2), 401–412. https://doi.org/10.1016/j.ejor.2008.05.007 Melo, M. T., Nickel, S., & Saldanha Da Gama, F. S. (2006). Dynamic multi-commodity capacitated facility location: A mathematical modeling framework for strategic supply chain planning. Computers and Operations Research, 33(1), 181–208. https://doi.org/10.1016/j.cor.2004.07.005 METRO CUADRADO. (2020). https://www.metrocuadrado.com/. https://www.metrocuadrado.com/ MINISTERIO DE SALUD Y PROTECCIÓN SOCIAL. (2013). RESOLUCIÓN 1604 DE 2013. Journal of Chemical Information and Modeling, 53(9), 1689–1699. Ministerio de Transporte. (2020). SICE-TAC. https://plc.mintransporte.gov.co/Runtime/empresa/ctl/SiceTAC/mid/417 Mousazadeh, M., Torabi, S. A., & Zahiri, B. (2015). A robust possibilistic programming approach for pharmaceutical supply chain network design. Computers and Chemical Engineering, 82, 115–128. https://doi.org/10.1016/j.compchemeng.2015.06.008 Rezapour, S., Farahani, R. Z., Dullaert, W., & De Borger, B. (2014). Designing a new supply chain for competition against an existing supply chain. Transportation Research Part E: Logistics and Transportation Review, 67, 124–140. https://doi.org/10.1016/j.tre.2014.04.005 Ross, A., & Jayaraman, V. (2008). An evaluation of new heuristics for the location of cross-docks distribution centers in supply chain network design. Computers and Industrial Engineering, 55(1), 64–79. https://doi.org/10.1016/j.cie.2007.12.001 Sadeghi, A., Sinaki, R. Y., Suer, G., & Çelikbilek, C. (2019). Fuzzy bi-objective model for a supply chain network design problem considering stochastic transportation leadtime. Procedia Manufacturing, 39(2019), 1517–1524. https://doi.org/10.1016/j.promfg.2020.01.296 Salehi Sadghiani, N., Torabi, S. A., & Sahebjamnia, N. (2015). Retail supply chain network design under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 75, 95–114. https://doi.org/10.1016/j.tre.2014.12.015 Shah, N. (2004). Pharmaceutical supply chains: Key issues and strategies for optimisation. Computers and Chemical Engineering, 28(6–7), 929–941. https://doi.org/10.1016/j.compchemeng.2003.09.022 Shamsuzzoha, A., Ndzibah, E., & Kettunen, K. (2020). Data-driven sustainable supply chain through centralized logistics network: Case study in a Finnish pharmaceutical distributor company. Current Research in Environmental Sustainability, 2, 100013. https://doi.org/10.1016/j.crsust.2020.100013 Shoja, A., Molla-Alizadeh-Zavardehi, S., & Niroomand, S. (2020). Hybrid adaptive simplified human learning optimization algorithms for supply chain network design problem with possibility of direct shipment. Applied Soft Computing Journal, 96, 106594. https://doi.org/10.1016/j.asoc.2020.106594 Singh, R. K., Chaudhary, N., & Saxena, N. (2018). Selection of warehouse location for a global supply chain: A case study. IIMB Management Review, 30(4), 343–356. https://doi.org/10.1016/j.iimb.2018.08.009 Singh, R. K., Kumar, R., & Kumar, P. (2016). Strategic issues in pharmaceutical supply chains: a review. International Journal of Pharmaceutical and Healthcare Marketing, 10(3), 234–257. https://doi.org/10.1108/IJPHM-10-2015-0050 Soysal, M., Bloemhof-Ruwaard, J. M., & Van Der Vorst, J. G. A. J. (2014). 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Designing logistics networks in divergent process industries: A methodology and its application to the lumber industry. International Journal of Production Economics, 102(2), 358–378. https://doi.org/10.1016/j.ijpe.2005.03.011 Wilhelm, W., Liang, D., Rao, B., Warrier, D., Zhu, X., & Bulusu, S. (2005). Design of international assembly systems and their supply chains under NAFTA. Transportation Research Part E: Logistics and Transportation Review, 41(6 SPEC. ISS.), 467–493. https://doi.org/10.1016/j.tre.2005.06.002 Yang, G., & Liu, Y. (2017). Optimizing an equilibrium supply chain network design problem by an improved hybrid biogeography based optimization algorithm. Applied Soft Computing Journal, 58, 657–668. https://doi.org/10.1016/j.asoc.2017.05.023 Yang, G. Q., Liu, Y. K., & Yang, K. (2015). Multi-objective biogeography-based optimization for supply chain network design under uncertainty. 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Design of a pharmaceutical supply chain network under uncertainty considering perishability and substitutability of products. Information Sciences, 423, 257–283. https://doi.org/10.1016/j.ins.2017.09.046 Zheng, X., Yin, M., & Zhang, Y. (2019). Integrated optimization of location, inventory and routing in supply chain network design. Transportation Research Part B: Methodological, 121, 1–20. https://doi.org/10.1016/j.trb.2019.01.003 |
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Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Castrellón Torres, Juan Pablocc43fc72edf560ae8fa005e362d644d8López Castillo, Iván Darío0e2f6c1903ae810b4a2f6e164f9ec0e4Grupo de investigación de operaciones de la Universidad Nacional de Colombia: UNGIDO2021-05-31T19:55:04Z2021-05-31T19:55:04Z2021-04https://repositorio.unal.edu.co/handle/unal/79577Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/diagramas, ilustraciones a color, mapas, tablasLa gestión de la cadena de abastecimiento principalmente se enfoca en alinear cada uno de los actores que la componen con el objetivo de maximizar el valor generado entre el costo del producto o servicio y su precio de venta, satisfaciendo así las necesidades de los clientes; sin embargo, en algunos sectores como el farmacéutico, este objetivo se orienta más hacia la maximización del valor para el cliente, ya que los productos farmacéuticos están relacionados en un 100% con la salud y el bienestar de las personas. Actualmente, la competitividad de los mercados está dada por la eficiencia de las cadenas de suministro y no por los productos directamente, por tanto, el diseño de la cadena de suministro tiene un alto grado de relevancia e importancia, siendo este un criterio decisivo a la hora de continuar en un mercado cada vez más competitivo. El desarrollo de este ejercicio se enfoca en determinar cuál debe ser la configuración de la cadena de suministro de productos farmacéuticos desde un enfoque de red saliente, tomando como caso de estudio un actor del sector farmacéutico colombiano, iniciando con un proceso de caracterización del modelo actual de abastecimiento, posteriormente se propone la configuración de red de abastecimiento identificando las posibles locaciones de las plataformas de abastecimiento que integran la red y se realiza la estructuración de costos fijos y variables asociados a la apertura de plataformas, el envío de producto desde plataformas a droguerías y el suministro del producto. Teniendo en cuenta la configuración de la red y los costos asociados, se desarrolló un modelo matemático para establecer las posibles configuraciones de red de abastecimiento en función de tiempo y costos. Este modelo es implementado por una herramienta computacional, generando como resultado una serie de configuraciones en función de los tiempos máximos de envío de la red que resultan ser óptimos bajo el objetivo de minimizar los costos totales. Por último, se propondrán recomendaciones en función de decisiones de tipo operativo, táctico y estratégico, las cuales podrán ser implementadas en corto, mediano y largo plazo, ya que, bajo los modelos propuestos, en el corto plazo se podrán proponer reducciones del 5% en los costos logísticos totales, en el mediano plazo, el servicio podrá optimizarse disminuyendo los tiempos de entrega de la red en un 6,5%, permitiendo no aumentar los costos totalesSupply chain management mainly focuses on aligning each of its actors with the objective of maximizing the value generated between the cost of the product or service and its sale price while satisfying customers’ needs. However, in some sectors, such as pharmaceuticals, this objective is more oriented towards maximizing customer value since pharmaceutical products are 100% related to people's health and well-being. Currently, market competitiveness is determined by supply chain efficiency and not directly by products. Therefore, supply chain design has a high degree of relevance and importance, this being a decisive criterion when it comes to continuing in an increasingly competitive market. The development of this exercise focuses on determining what the supply chain configuration of pharmaceutical products should be from an outgoing network approach, while taking as a case study an actor from the Colombian pharmaceutical sector. This study will start with a characterization process of the current supply chain model. It will subsequently propose the supply chain configuration by identifying possible locations of the supply platforms that make up the network and the structuring of fixed and variable costs associated with the opening of these platforms, the shipment of product from platforms to drugstores and product supply. Taking into account the network configuration and associated costs, a mathematical model was developed to establish the possible supply chain network configurations based on time and costs. This model is implemented by a computational tool, resulting in a series of configurations based on the maximum network sending times that are optimal under the objective of minimizing total costs. Finally, recommendations will be proposed based on operational, tactical, and strategic decisions, which may be implemented in the short, medium, and long term. Under the proposed models, reductions of 5% may be proposed in the short term regarding total logistics costs. While in the medium term, the service can be optimized by reducing network delivery times by 6.5%, thus allowing no increase in total costs.MaestríaMagíster en Ingeniería - Ingeniería IndustrialEl tipo de investigación que se va a desarrollar es un Estudio de Caso donde se busca estudiar en profundidad una unidad de análisis específica, tomada de un universo poblacional (Bernal, 2016), para el desarrollo de este trabajo se toma como caso o unidad de análisis una empresa del sector farmacéutico de Colombia. El enfoque de investigación de este trabajo es desarrollado bajo una metodología mixta con un enfoque Secuencial Exploratorio .Investigación de operaciones1 recurso en línea (155 páginas)application/pdfspaUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería IndustrialDepartamento de Ingeniería de Sistemas e IndustrialFacultad de IngenieríaBogotáUniversidad Nacional de Colombia - Sede Bogotá620 - Ingeniería y operaciones afinesLogísticaLogisticsCanales de distribuciónDistribution channelsDiseño de cadena de suministroCentros de abastecimiento y distribuciónModo de transporteTiempos de entregaCostos logísticosSupply Chain Network DesignSCNDDistribution CentersMode of transportLead timeLogistics CostsPropuesta de la configuración de la red logística de productos farmacéuticos bajo los criterios de costos y tiempos de respuestaProposal for the configuration of a logistics network of pharmaceutical products under the criteria of costs and response timesTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAlzaman, C., Zhang, Z. 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Transportation Research Part B: Methodological, 121, 1–20. https://doi.org/10.1016/j.trb.2019.01.003LICENSElicense.txtlicense.txttext/plain; charset=utf-83964https://repositorio.unal.edu.co/bitstream/unal/79577/1/license.txtcccfe52f796b7c63423298c2d3365fc6MD51ORIGINAL1016028402.2021.pdf1016028402.2021.pdfTesis de Maestría en Ingeniería - Ingeniería Industrialapplication/pdf3720438https://repositorio.unal.edu.co/bitstream/unal/79577/2/1016028402.2021.pdf01c83e235e0c2c2c293da339b086db2dMD521016028402.2021-Instrumento_Entrevista_Experto.pdf1016028402.2021-Instrumento_Entrevista_Experto.pdfAnexo: Instrumento Entrevista Expertoapplication/pdf86932https://repositorio.unal.edu.co/bitstream/unal/79577/3/1016028402.2021-Instrumento_Entrevista_Experto.pdf803cbd6853f317f0d9b95bb67f69956bMD531016028402.2021-MODELO_OPTIMIZACION.rar1016028402.2021-MODELO_OPTIMIZACION.rarAnexo: Modelo 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