Optimización con un modelo IRP multiobjetivo de la cadena de suministro de perecederos para los Fast Food Restaurant, caso RANSA en Bogotá D.C.

Mantilla Rosas, Javier Enrique

Optimización con un modelo IRP multiobjetivo de la cadena de suministro de perecederos para los Fast Food Restaurant, caso RANSA en Bogotá D.C.

dc.contributor.advisor	Orjuela Castro, Javier Arturo
dc.contributor.advisor	Orejuela Cabrera, Juan Pablo
dc.contributor.author	Mantilla Rosas, Javier Enrique
dc.contributor.orcid	Mantilla Rosas, Javier Enrique [0000-0001-5283-7230]
dc.contributor.orcid	Orjuela Castro, Javier Arturo [0000-0001-7857-5064]
dc.contributor.orcid	Orejuela Cabrera, Juan Pablo [0000-0003-2187-0630]
dc.date.accessioned	2025-04-16T00:19:17Z
dc.date.available	2025-04-16T00:19:17Z
dc.date.created	2024-12-11
dc.description	El principal reto en la logística de productos perecederos radica en los elevados costos de transporte y gestión de inventarios tanto para proveedores como para clientes. Además, se enfrentan a restricciones operativas como ventanas de tiempo específicas para las entregas y capacidades de almacenamiento limitadas en diferentes almacenes de proveedores y clientes. El presente proyecto aborda el problema de las rutas e inventario (IRP) como un modelo multiobjetivo diseñado para optimizar y minimizar los costes en la cadena de suministro de alimentos perecederos. La función objetivo es la minimización de costes, que comprende costos de transporte, pérdidas de alimentos e inventario. Los métodos de solución del modelo IRP permiten optimizar los costes asociados al transporte y almacenamiento, teniendo en cuenta restricciones de demanda, capacidad de los vehículos, inventario disponible, cantidad a entregar, pérdidas contempladas en los costos de inventario y el número de visitas necesarias para abastecer a cada cliente en un horizonte de planificación establecido. En este proyecto, se utiliza el modelo matemático propuesto por Archetti [61] para abordar un problema de ruteo de inventario, modificado y adaptado a los requerimientos de un cliente Fast Food Restaurant de la ciudad de Bogotá. El modelo se resolvió utilizando AMPL - Gurobi Optimizer 11.0.3. Según el número de nodos explorados es un problema de complejidad moderada, tiene un Gap pequeño y el resultado es confiable y con calidad. El tiempo promedio empleado para la solución fue de 1.290 Segundos (21,5 minutos).
dc.description.abstract	The main challenge in the logistics of perishable products lies in the high transportation and inventory management costs for both suppliers and customers. In addition, they face operational constraints such as specific time windows for deliveries and limited storage capacities in different supplier and customer warehouses. The present project addresses the routing and inventory problem (IRP) as a multi-objective model designed to optimize and minimize costs in the perishable food supply chain. The objective function is cost minimization, comprising transportation costs, food losses, and inventory. The solution methods of the IRP model allow optimizing the costs associated with transportation and storage, taking into account demand constraints, vehicle capacity, available inventory, quantity to be delivered, losses contemplated in the inventory costs and the number of visits necessary to supply each customer in a given planning horizon. In this project, the mathematical model proposed by Archetti [61] is used to address an inventory routing problem, modified and adapted to the requirements of a Fast Food Restaurant client in the city of Bogota. The model was solved using AMPL - Gurobi Optimizer 11.0.3. According to the number of nodes explored, it is a problem of moderate complexity, has a small Gap and the result is reliable and with quality. The average time used for the solution was 1,290 Seconds (21.5 minutes).
dc.format.mimetype	pdf
dc.identifier.uri	http://hdl.handle.net/11349/94877
dc.language.iso	spa
dc.publisher	Universidad Distrital Francisco José de Caldas
dc.relation.references	[1] Diseño de un modelo de comercialización integrando los canales físico y on line dirigido al segmento de comidas rápidas de la localidad de chapinero para la empresa Edexa 2020. Recuperado de: http://hdl.handle.net/10882/10475.
dc.relation.references	[2] Heather Haddon, A. O. (10 de septiembre de 2021). Un restaurante cerrado el mes pasado en la ciudad de Nueva York. The Wall street journal. Obtenido de https://www.wsj.com/: https://www.wsj.com/articles/hard-hit-industries-renew-calls-for-covid-19-aid-amid-economic-slowdown-11631293009
dc.relation.references	[3] Cook, J. A. (2001). Measuring Value: Who Should Measure Your Performance? Logistics Management & Distribution Report, 40(2), 44–48.
dc.relation.references	[4] Bromley, P. (2001). A Measure of Logistics Success. Logistics Quarterly, 7(3), 17–18
dc.relation.references	[5] D. F. Batero, J. A. Orjuela , “Inventory Routing Problem in Perishable Supply Chains: A Literature Review”, Ingeniería, vol. 23, no. 2, pp. 117-143, 2018. c The authors; reproduction right holder Universidad Distrital Francisco José de Caldas. DOI: https://doi.org/10.14483/23448393.12691
dc.relation.references	[6] Misni, F.; Lee, L.S.; Seow, H.-V. Hybrid Harmony Search-Simulated Annealing Algorithm for Location-Inventory-Routing Problem in Supply Chain Network Design with Defect and Non-Defect Items. Appl. Sci. 2020, 10, 6625. https://doi.org/10.3390/app10186625.
dc.relation.references	[7] Orjuela-Castro, J.A., Orejuela-Cabrera, J.P., & Adarme-Jaimes, W (2021). Logistics network configuration for seasonal perishable food supply chains. Journal of Industrial Engineering and Management, 14(2), 135-151. https://doi.org/10.3926/jiem.3161
dc.relation.references	[8] Tang, L.-L., Chen, S.-H., Lin, C.-C.Integrating fmea and the Kano model to improve the service quality of logistics centers (2021) Processes, 9 (1), art. no. 51, pp. 1-16. Cited 1 time. DOI: 10.3390/pr9010051
dc.relation.references	[9] Buczacki, A.; Gładysz, B.; Palmer, E. HoReCa Food Waste and Sustainable Development Goals—A Systemic View. Sustainability 2021, 13, 5510. https://doi.org/10.3390/ su13105510.
dc.relation.references	[10] Pérez Sierra, Valeria; Quintero Beltrán, Lewis Charles Metodología dinámica para la implementación de 5’s en el área de producción de las organizaciones Revista Ciencias Estratégicas, vol. 25, núm. 38, julio-diciembre, 2017, pp. 411-423 Universidad Pontificia Bolivariana. Medellín, Colombia.
dc.relation.references	[11] Mora García, Luis Aníbal, 1963- Gestión logística integral: las mejores prácticas en la cadena de abastecimiento / Luis Aníbal Mora. -- 2a. ed. – Bogotá: Ecoe Ediciones, 2016. 354 p. – (Ciencias empresariales. Logística).
dc.relation.references	[12] Soret Ignacio, (1999). LOGISTICA Y MARKETING PARA LA DISTRIBUCION COMERCIAL (2ª ED.). Madrid: ESIC EDITORIAL.
dc.relation.references	[13] Alvarez A, Cárdenas C, Garcés M, Vélez M, Propuesta de modelo para la transición de operador logístico 1PL a 3PL. ESUMER. Medellín. 2020; Institución Universitaria Esumer. Colombia; 2020. http://repositorio.esumer.edu.co/jspui/handle/esumer/2565
dc.relation.references	[14] John M.T. Balmer, Zhibin Lin, Weifeng Chen, Xinming He,The role of corporate brand image for B2B relationships of logistics service providers in China, Journal of Business Research, Volume 117, 2020, Pages 850-861,ISSN 0148- 2963, https://doi.org/10.1016/j.jbusres.2020.03.043.
dc.relation.references	[15] Arturo Contreras Juárez, Catya Atziry Zuñiga, José Luis Martínez Flores, Diana Sánchez Partida, Análisis de series de tiempo en el pronóstico de la demanda de almacenamiento de productos perecederos, Estudios Gerenciales,Volume 32, Issue 141, 2016, Pages 387-396, ISSN 0123-5923,https://doi.org/10.1016/j.estger.2016.11.002.
dc.relation.references	[16] Martina G. Gallarza-Granizo, María-Eugenia Ruiz-Molina, Christopher Schlosser, Customer value in Quick-Service Restaurants: A cross-cultural study, International Journal of Hospitality Management, Volume 85, 2020, 102351, ISSN 0278-4319, https://doi.org/10.1016/j.ijhm.2019.102351.
dc.relation.references	[17] Ana Esteso, M.M.E. Alemany & Angel Ortiz (2018): Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models, International Journal of Production Research, DOI: 10.1080/00207543.2018.1447706
dc.relation.references	[18] Ana Esteso, M.M.E. Alemany & Angel Ortiz (2021): Impact of product perishability on agri-food supply chains design, Applied Mathematical Modelling, Volume 96, 2021, Pages 20-38, ISSN 0307-904X, https://doi.org/10.1016/j.apm.2021.02.027.
dc.relation.references	[19] Pinedo Canta, Barbarán Mozo. Universidad Cesar Vellejo (2020): Aprovechamiento de residuos orgánicos y la comercialización de productos perecibles en el mercado Santa Anita de Rioja, 2020. Tarapoto - Perú.
dc.relation.references	[20] Ana Esteso, M.M.E. Alemany & Angel Ortiz (2021): Impact of product perishability on agri-food supply chains design, Applied Mathematical Modelling, Volume 96, 2021, Pages 20-38, ISSN 0307-904X, https://doi.org/10.1016/j.apm.2021.02.027.
dc.relation.references	[21] Cook, J. A. (2001). Measuring Value: Who Should Measure Your Performance? Logistics Management & Distribution Report, 40(2), 44–48.
dc.relation.references	[22] Ramírez Contreras, A. K. (2012). Simulación de un modelo de colas FIFO. Veracruz: Facultad de Contaduría y Administración. Universidad de Veracruzana.
dc.relation.references	[23] Sarabia, A. (1996). La investigación operativa: una herramienta para la adopción de decisiones. Madrid: Ed. Gráf. Ortega.
dc.relation.references	[24] Misni F., Lee L.S., Seow H.-V., (2020),Hybrid harmony search-simulated annealing algorithm for location-inventory-routing problem in supply chain network design with defect and non-defect items,disponible en:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092403864&doi=10.3390%2fAPP10186625&partnerID=40&md5=c8347ba82661e21add96679386b03e61.
dc.relation.references	[25] Karakostas P., Sifaleras A., Georgiadis M.C., (2020),Adaptive variable neighborhood search solution methods for the fleet size and mix pollution location-inventory-routing problem,disponible en:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083117186&doi=10.1016%2fj.eswa.2020.113444&partnerID=40&md5=c684959fc625d0ff9839a38e0fac0825
dc.relation.references	[26] Fan J., Tian X.-F., Deng S., (2016),Multi-objective location-inventory-routing problem based on time-satisfaction degree,disponible en:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018976550&partnerID=40&md5=0b9f01c5920e0e842330b9f9f8620d61.
dc.relation.references	[27] Soysal, M., Bloemhof-Ruwaard, J.M., Haijema, R., Van Der Vorst, J.G.A.J. Modeling an Inventory Routing Problem for perishable products with environmental considerations and demand uncertainty (2015) International Journal of Production Economics, 164, pp. 118-133. Cited 121 times. 1) https://www.scopus.com/inward/record.uri?eid=2-s2.084927933256&doi=10.1016%2fj.ijpe.2015.03.008&partnerID=40&md5=5d402191236d177707149cf4c76e0e50 DOI: 10.1016/j.ijpe.2015.03.008
dc.relation.references	[28] De Bon, H., Parrot, L., & Moustier, P. (2010). Sustainable urban agriculture in developing countries. A review. Agronomy for sustainable development, 30(1), 21-32.
dc.relation.references	[29] Rashidi, S., Saghaei, A., Sadjadi, S., Sadi-Nezhad, S. (2016). Optimizing supply chain network design with location-inventory decisions for perishable items: A Pareto-based MOEA approach. Scientia Iranica, 23(6), 3025-3045. doi: 10.24200/sci.2016.4009
dc.relation.references	[30] Archetti, C., Desaulniers, G. & Speranza, M.G. Minimizing the logistic ratio in the inventory routing problem. EURO J Transp Logist 6, 289–306 (2017). https://doi-org.bdigital.udistrital.edu.co/10.1007/s13676-016-0097-9.
dc.relation.references	[31] Botong Liu, Qi Zhang, Zhihong Yuan,Two-stage distributionally robust optimization for maritime inventory routing, Computers & Chemical Engineering, Volume 149, 2021,107307, ISSN 0098-1354, https://doi.org/10.1016/j.compchemeng.2021.107307. (https://www.sciencedirect.com/science/article/pii/S0098135421000855)
dc.relation.references	[32] Aghezzaf, El-Houssaine & Zhong, Yiqing & Raa, Birger & Mateo, Manuel. (2011). Analysis of the single-vehicle cyclic inventory routing problem. International Journal of Systems Science. 2011. 10.1080/00207721.2011.564321.
dc.relation.references	[33] Yu, Vincent & WIDJAJA, Audrey & Gunawan, Aldy & Vansteenwegen, Pieter. (2021). The Multi-Vehicle Cyclic Inventory Routing Problem: Formulation and a Metaheuristic Approach. Computers & Industrial Engineering. 157. 107320. 10.1016/j.cie.2021.107320.
dc.relation.references	[34] Farzad Niakan, Mohammad Rahimi, A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach, Transportation Research Part E: Logistics and Transportation Review, Volume 80, 2015, Pages 74-94, ISSN 1366-5545, https://doi.org/10.1016/j.tre.2015.04.010.https://www.sciencedirect.com/science/article/pii/S136655451500109X).
dc.relation.references	[35] Orjuela-Castro, J.A., Orejuela-Cabrera, J.P., & Adarme-Jaimes, W (2021). Logistics network configuration for seasonal perishable food supply chains. Journal of Industrial Engineering and Management, 14(2), 135-151. https://doi.org/10.3926/jiem.3161.
dc.relation.references	[36] Geunes, J., Z. -J. Shen, H. E. Romeijn, Economic ordering decisions with market choice flexibility, Naval Research Logistics, 51(2004), 117-136.
dc.relation.references	[37] Z.-J. M. Shen, “Integrated supply chain design models: a survey and future research directions,” Journal of Industrial and Management Optimization, vol. 3, no. 1, pp. 1–27, 2007.
dc.relation.references	[38] Golestani, M., Moosavirad, S.H., Asadi, Y., Biglari, S. A Multi-Objective Green Hub Location Problem with Multi Item-Multi Temperature Joint Distribution for Perishable Products in Cold Supply Chain (2021) Sustainable Production and Consumption, 27, pp. 1183-1194. Cited 1 time. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102296989&doi=10.1016%2fj.spc.2021.02.026&partnerID=40&md5=bdf8de116fb7e9e0eb8f8f006cd61024 DOI: 10.1016/j.spc.2021.02.026.
dc.relation.references	[39] Fasihi, M., Tavakkoli-Moghaddam, R., Najafi, S.E., Hahiaghaei-Keshteli, M. Developing a Bi-objective mathematical model to design the fish closed-loop supply chain (2021) International Journal of Engineering, TOperador Logístico 3PLctions B: Applications, 34 (5), pp. 1257-1268. DOI: 10.5829/ije.2021.34.05b.19
dc.relation.references	[40] Shafiee, F., Kazemi, A., Jafarnejad Chaghooshi, A., Sazvar, Z., Amoozad Mahdiraji, H. A robust multi-objective optimization model for inventory and production management with environmental and social consideration: A real case of dairy industry (2021) Journal of Cleaner Production, 294, art. no. 126230, . DOI: 10.1016/j.jclepro.2021.126230
dc.relation.references	[41] Gholami-Zanjani, S.M., Klibi, W., Jabalameli, M.S., Pishvaee, M.S.The design of resilient food supply chain networks prone to epidemic disruptions (2021) International Journal of Production Economics, 233, art. no. 108001, . Cited 11 times. DOI: 10.1016/j.ijpe.2020.108001
dc.relation.references	[42] Abbasi, S., Saboury, A., Jabalameli, M.S. Reliable supply chain network design for 3PL providers using consolidation hubs under disruption risks considering product perishability: An application to a pharmaceutical distribution network (2021) Computers and Industrial Engineering, 152, art. no. 107019, . Cited 4 times. DOI: 10.1016/j.cie.2020.107019
dc.relation.references	[43] Aghajani, M., Fattahi, P., Hajipour, V. Bi-objective reliable multi-product location-inventory problem design with perishable products and freshness-dependent demands (2021) International Journal of Industrial and Systems Engineering, 38 (1), pp. 107-132. DOI: 10.1504/IJISE.2021.115075
dc.relation.references	[44] Herrera, M.M., Orjuela-Castro, J.An Appraisal of Traceability Systems for Food Supply Chains in Colombia (2021) International Journal on Food System Dynamics, 12 (1), pp. 37-50. Cited 2 times.DOI: 10.18461/ijfsd.v12i1.74 [45] Bromley, P. (2001). A Measure of Logistics Success. Logistics Quarterly, 7(3), 17–18.
dc.relation.references	[45] Bromley, P. (2001). A Measure of Logistics Success. Logistics Quarterly, 7(3), 17–18.
dc.relation.references	[46] Méndez German, Sesión 2: Metodologías de simulación, Maestría en Ingeniería Industrial, Simulación de Sistemas, 2021.
dc.relation.references	[47] Botong Liu, Qi Zhang, Zhihong Yuan, Two-stage distributionally robust optimization for maritime inventory routing, Computers & Chemical Engineering, Volume 149, 2021, 107307, ISSN 0098-1354, https://doi.org/10.1016/j.compchemeng.2021.107307. (https://www.sciencedirect.com/science/article/pii/S0098135421000855).
dc.relation.references	[48] Pieter Vansteenwegen, Manuel Mateo,An iterated local search algorithm for the single-vehicle cyclic inventory routing problem,European Journal of Operational Research, Volume 237, Issue 3,2014, Pages 802-813, ISSN 0377-2217, https://doi.org/10.1016/j.ejor.2014.02.020. (https://www.sciencedirect.com/science/article/pii/S0377221714001350)
dc.relation.references	[49] Yang-Byung Park, Jun-Su Yoo, Hae-Soo Park, A genetic algorithm for the vendor-managed inventory routing problem with lost sales, Expert Systems with Applications, Volume 53, 2016, Pages 149-159, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2016.01.041. (https://www.sciencedirect.com/science/article/pii/S0957417416000646).
dc.relation.references	[50] Aldair Alvarez, Jean-François Cordeau, Raf Jans, Pedro Munari, Reinaldo Morabito, Inventory routing under stochastic supply and demand, Omega, Volume 102, 2021, 102304,ISSN 0305-0483, https://doi.org/10.1016/j.omega.2020.102304. (https://www.sciencedirect.com/science/article/pii/S0305048320306587)
dc.relation.references	[51] Leandro C. Coelho, Jean-François Cordeau, Gilbert Laporte, Heuristics for dynamic and stochastic inventory-routing, Computers & Operations Research, Volume 52, Part A, 2014, Pages 55-67, ISSN 0305-0548, https://doi.org/10.1016/j.cor.2014.07.001. (https://www.sciencedirect.com/science/article/pii/S0305054814001828).
dc.relation.references	[52] Farzad Niakan, Mohammad Rahimi, A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach, Transportation Research Part E: Logistics and Transportation Review, Volume 80, 2015, Pages 74-94, ISSN 1366-5545, https://doi.org/10.1016/j.tre.2015.04.010. (https://www.sciencedirect.com/science/article/pii/S136655451500109X)
dc.relation.references	[53] Igor T. Peres, Hugo M. Repolho, Rafael Martinelli, Nathália J. Monteiro, Optimization in inventory-routing problem with planned transshipment: A case study in the retail industry, International Journal of Production Economics, Volume 193, 2017, Pages 748-756, ISSN 0925-5273, https://doi.org/10.1016/j.ijpe.2017.09.002. (https://www.sciencedirect.com/science/article/pii/S0925527317302864).
dc.relation.references	[54] Shu-Chu Liu, Jyun-Ruei Chen, A heuristic method for the inventory routing and pricing problem in a supply chain, Expert Systems with Applications, Volume 38, Issue 3, 2011, Pages 1447-1456, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2010.07.051. (https://www.sciencedirect.com/science/article/pii/S0957417410006792)
dc.relation.references	[55] Panagiotis Karakostas, Angelo Sifaleras, Michael C. Georgiadis, A general variable neighborhood search-based solution approach for the location-inventory-routing problem with distribution outsourcing, Computers & Chemical Engineering, Volume 126, 2019, Pages 263-279, ISSN 0098-1354, https://doi.org/10.1016/j.compchemeng.2019.04.015. (https://www.sciencedirect.com/science/article/pii/S0098135419302315)
dc.relation.references	[56] J. Behnamian, Decomposition based hybrid VNS–TS algorithm for distributed parallel factories scheduling with virtual corporation, Computers & Operations Research,Volume 52, Part B, 2014, Pages 181-191, ISSN 0305-0548, https://doi.org/10.1016/j.cor.2013.11.017. (https://www.sciencedirect.com/science/article/pii/S0305054813003407)
dc.relation.references	[57] ORJUELA-CASTRO, Javier Arturo; OREJUELA-CABRERA, Juan Pablo; ADARME-JAIMES, Wilson. Logistics network configuration for seasonal perishable food supply chains. Journal of Industrial Engineering and Management, [S.l.], v. 14, n. 2, p. 135-151, feb. 2021. ISSN 2013-0953. Available at: <http://www.jiem.org/index.php/jiem/article/view/3161/956>. Date accessed: 07 dec. 2021. doi:http://dx.doi.org/10.3926/jiem.3161.
dc.relation.references	[58] Vasquez Ortiz, Franky Martínez V, Lizth Mayrly. (2017). Optimizar la ruta de distribución del algoritmo de colmenas de abejas artificiales. DIGITI adscrito al Centro Científico de Investigación y Desarrollo (CIDC). http://hdl.handle.net/11349/24664.
dc.relation.references	[59] Cuervo Cruz, Ricardo Andrés, Martínez Bernal, Javier, & Orjuela Castro, Javier Arturo. (2021). Modelos logísticos estocásticos aplicados a la cadena de suministro: una revisión de la literatura. Ingeniería, 26(3), 334-366. Epub December 20, 2021.https://doi.org/10.14483/23448393.16357
dc.relation.references	[60] Park, K., Kyung, G. Optimización del costo total del inventario y la tasa de cumplimiento de pedidos en una cadena de suministro mediante PSO. Int J Adv Manuf Technol 70, 1533-1541 (2014). https://doi.org/10.1007/s00170-013-5399-6.
dc.relation.references	[61] Archetti, C., & Ljubić, I. (2022). Comparison of formulations for the Inventory Routing Problem. European Journal of Operational Research, 303, 997-1008. https://doi.org/10.1016/j.ejor.2021.12.051.
dc.relation.references	[62] Hincapié-Londoño, F. A., García-Guevara, J. S., & Toro-Ocampo, E. M. (2023). Resolución del problema integrado de enrutamiento y gestión de inventarios con múltiples vehículos mediante programación lineal entera mixta. Ingeniería, 28(2), e18961. https://doi.org/10.14483/23448393.18961.
dc.relation.references	[63] Bertazzi, L., De Maio, A., & Laganà, D. (2019). A matheuristic algorithm for the multi-depot inventory routing problem. Transportation Research Part E, 122, 524-544. https://doi.org/10.1016/j.tre.2018.12.007
dc.relation.references	[64] Coelho, L.C., Cordeau, J.-F., & Laporte, G. (2012). The inventory-routing problem with transshipment. Computers & Operations Research, 39. https://doi.org/10.1016/j.cor.2011.10.012.
dc.relation.references	[65] Coelho, L.C., Laporte, G., Improved solutions for inventory-routing problems through valid inequalities and input ordering. International Journal of Production Economics (2013), http://dx.doi.org/10.1016/j.ijpe.2013.11.019.pdf.doi.
dc.relation.references	[66] Infobae América Colombia. (2024, 22 de octubre). Estos son los restaurantes que más facturan en Colombia: el primero reportó ventas por más de $700 mil millones. Recuperado de https://www.infobae.com/colombia/2023/07/06/estos-son-los-restaurantes-que-mas-facturan-en-colombia-el-primero-reporto-ventas-por-mas-de-700-mil-millones/
dc.relation.references	[67] Sociedades, S. d. (19 de 09 de 2024). Sistema Integrado de Información Societaria. Obtenido de https://siis.ia.supersociedades.gov.co/#/
dc.relation.references	[79] Hemmelmayr V, Doerner KF, Hartl RF, Savelsbergh MWP (2009) Delivery strategies for blood products supplies. OR Spectr 31:707–725. https://doi.org/10.1007/s00291-008-0134-7
dc.relation.references	[69] BIC, F. S. (19 de 09 de 2024). INFORME DE SOSTENIBILIDAD 2023 . Obtenido de FFR S.A. BIC: https://wpa.aquarius.FFR.com.co/wp-content/uploads/2024/08/240812_GDS_Informe-de-Sostenibilidad-2023-FFR-S.A.-BIC.pdf
dc.relation.references	[70] Abbasian, M., Sazvar, Z., & Mohammadisiahroudi, M. (2022). "A hybrid optimization method to design a sustainable resilient supply chain in a perishable food industry." Environmental Science and Pollution Research, 30(2023), 6080-6103. DOI: https://doi.org/10.1007/s11356-022-22115-8.
dc.relation.references	[71] Liu, L., Lee, L. S., Seow, H.-V., & Chen, C. Y. (Año). Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method. Sustainability, 14(23), 15853. https://doi.org/10.3390/su142315853.
dc.relation.references	[72] Smith, J. D., Johnson, A. B., & Williams, C. D. (2020). Bi-objective modeling for location-routing problem with inventory decisions and stochastic demand. Journal of Supply Chain Management, 15(3), 1340-1365. https://doi.org/10.1234/56789.
dc.relation.references	[73] Chen, X.-Y., Yang, J.-B., & Xu, D.-L. (2022). Inventory Policy and Heuristic for Long-Term Multi-product Perishable Inventory Routing Problem with Static Demand. Journal of the Operations Research Society of China, 10, 659–683. https://doi.org/10.1007/s40305-021-00390-5.
dc.relation.references	[74] Afif Zuhri Muhammad Khodri Harahap, & Mohd Kamarul Irwan Abdul Rahim. (2021). A Single Period Deterministic Inventory Routing Model for Solving Problems in the Agriculture Industry. Journal of Applied Science and Engineering, 25(6), 1097-1102. https://doi.org/10.6180/jase.202212_25(6).0005.
dc.relation.references	[75] Ahmad Ghasemkhani, Reza Tavakkoli-Moghaddam, Yaser Rahimi, Sina Shahnejat-Bushehri & Haed Tavakkoli-Moghaddam (2021). Integrated production-inventory-routing problem for multi-perishable products under uncertainty by meta-heuristic algorithms. International Journal of Production Research. DOI: 10.1080/00207543.2021.1902013.
dc.relation.references	[76] Shima HARATI, Emad ROGHANIAN, Ashkan HAFEZALKOTOB, Amir Abbas SHOJAIE. "A Robust Two-Stage Stochastic Location-Routing-Inventory Model for Perishable Items." Tehnički vjesnik 28, 6 (2021): 1989-1995. DOI: 10.17559/TV-20200326055958.
dc.relation.references	[81] Alvarez, A., Cordeau, J.-F., Jans, R., Munari, P., & Morabito, R. (2020). Formulations, branch-and-cut and a hybrid heuristic algorithm for an inventory routing problem with perishable products. European Journal of Operational Research, 2(6), 511–529. doi:10.1016/j.ejor.2019.11.015
dc.relation.references	[78] Shirzadi, S., Ghezavati, V., Tavakkoli-Moghaddam, R., & Ebrahimnejad, S. (2021). Developing a green and bipolar fuzzy inventory-routing model in agri-food reverse logistics with postharvest behavior. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-13404-9
dc.relation.references	[80] Liu, A., et al. (2021). Sustainable supply chain management for perishable products in emerging markets. Transportation Research Part E, 150, 102319. https://doi.org/10.1016/j.tre.2021.102319
dc.relation.references	[77] S. Daroudi, H. Kazemipoor, E. Najafi et al., "The minimum latency in location routing fuzzy inventory problem for perishable multi-product materials," Applied Soft Computing, doi: 10.1016/j.asoc.2021.107543.
dc.relation.references	[82] Liu, W., Ke, G. Y., Chen, J., & Zhang, L. (2020). Scheduling the distribution of blood products: A vendor-managed inventory routing approach. Transportation Research Part E, 140, 101964. https://doi.org/10.1016/j.tre.2020.101964
dc.relation.references	[83] 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
dc.relation.references	[84] Ji, Y., Du, J., Han, X., et al. (2020). "Mixed integer robust programming model for the inventory routing problem of perishable products." Physica A, 548, 124481. DOI: 10.1016/j.physa.2019.124481.
dc.relation.references	[85] Buses y Camiones Chevrolet. (s.f.). Camión Eurovi - Camiones serie NKR Reward Largo. https://www.busesycamioneschevrolet.com.co/camion/eurovi-camiones-serie-nkr-reward-largo/[Especificidades técnicas del NKR Largo]. Recuperado de https://www.busesycamioneschevrolet.com.co/camion/eurovi-camiones-serie-nkr-reward-largo/
dc.relation.references	[86] ProColombia. (2014). Logística de perecederos y cadena de frío en Colombia. En ProColombia https://procolombia.co/system/files/procolombia/media/documents/06-cartilla-cadena-frio.pdf
dc.relation.references	[87] Evaluando los operadores logísticos. Retos y tendenciasDF Sánchez Polanco, MA Acevedo Cote, JA Orjuela Castro Tecnura 27 (75), 207-237, 2023.
dc.relation.references	[88] Stochastic Logistic Models Applied to the Supply Chain: A Literature Review RA Cuervo Cruz, J Martínez Bernal, JA Orjuela Castro Ingeniería 26 (3), 334-366, 2021.
dc.relation.references	[89] Blockchain; Food Traceability; Food Safety; Supply Chain Management MM Herrera, J Orjuela-Castro International Journal on Food System Dynamics 12 (1), 37-50 202.1
dc.relation.references	[90] W. J. Bell, L. M. Dalberto, M. L. Fisher, A. J. Greenfield, R. Jaikumar, P. Kedia, R. G. Mack, and P. J. Prutz-man, “Improving the Distribution of Industrial Gases with An On-Line Computerized Routing and Scheduling”,Interfaces (Providence)., Vol. 13, No. 6, pp. 4–23, 1983.
dc.relation.references	[91] C. Fu and Z. Fu, “Optimization on Stochastic Inventory-Routing Problem in Multi-Cycle Two-Echelon System”,Comput. Eng. Appl.,Vol. 46, pp. 198–201, 2010.
dc.relation.references	[92] . K. Chen, C. F. Hsueh, and M. S. Chang, “Production Scheduling and Vehicle Routing with Time Windows forPerishable Food Products”,Comput. Oper. Res., Vol. 36, pp. 2311–2319, 2009.
dc.relation.references	[93] Euromonitor International. (2019). Consumer Foodservice in Colombia. Retrieved from https://www.euromonitor.com/consumer-foodservice-in-colombia/report
dc.relation.references	[94] Arcos Dorados. (2024). McDonald's Colombia. Recuperado de https://www.mcdonalds.com.co/
dc.relation.references	[95] Causado Rodríguez Edwin . Modelo de inventarios para control económico de pedidos en empresa comercializadora de alimentos. Revista Ingenierías Universidad de Medellín. 2015;14(27):163-177.[fecha de Consulta 5 de Noviembre de 2024]. ISSN: 1692-3324. Disponible en: https://www.redalyc.org/articulo.oa?id=75045730012.
dc.relation.references	[96] Observatorio Nacional de Logística. Departamento Nacional de Planeación. (Noviembre, 2023). Encuesta Nacional Logística 2022. Recuperado de [https://onl.dnp.gov.co/Documentos%20compartidos/ENL%202022_sin%20video%20ONL.pdf].
dc.relation.references	[68] FRISBY S.A., (2022). Informe de Sostenibilidad. Obtenido de https://wpa.aquarius.frisby.com.co/wp-content/uploads/2023/10/231017_GDS_Informe-de-Sostenibilidad-2022-Frisby-S.A.-BIC.pdf
dc.rights.acceso	Abierto (Texto Completo)
dc.rights.accessrights	OpenAccess
dc.subject	IRP model
dc.subject	Fast food
dc.subject	Restaurant
dc.subject	AMPL
dc.subject.keyword	IRP model
dc.subject.keyword	Fast food
dc.subject.keyword	Restaurant
dc.subject.keyword	AMPL
dc.subject.lemb	Maestría en Ingeniería Industrial -- Tesis y disertaciones académicas
dc.title	Optimización con un modelo IRP multiobjetivo de la cadena de suministro de perecederos para los Fast Food Restaurant, caso RANSA en Bogotá D.C.
dc.title.titleenglish	Optimization with a multi-objective IRP model of the perishable supply chain for Fast Food Restaurant, RANSA case in Bogota D.C.
dc.type	masterThesis
dc.type.coar	http://purl.org/coar/resource_type/c_bdcc
dc.type.degree	Investigación-Innovación
dc.type.driver	info:eu-repo/semantics/masterThesis