An optimization approach for inventory costs in probabilistic inventory models: A case study

Inventories represent stocks of goods necessary for operations of sales or manufacturing in a company. These allow to the companies meet their sales levels, while representing an opportunity to the cost control and the decision-making. This paper presents an optimization approach to minimize the inv...

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Autores:
Pulido-Rojano, Alexander
Andrea, Andrea
Padilla-Polanco, Miguel
Sánchez-Jiménez, Milton
De la-Rosa, Ladianys
Tipo de recurso:
Fecha de publicación:
2020
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/6620
Acceso en línea:
https://hdl.handle.net/20.500.12442/6620
https://www.ingeniare.cl/index.php?option=com_ingeniare&view=d&doc=106/03-_PULIDO-ROJANO-28-3_ultima_version.pdf&aid=799&vid=106&lang=es
Palabra clave:
Probabilistic inventory models
Independent demand
Safety stock
Forecasting methods
Total cost of inventory
Dispersion of demand
Modelos de inventario probabilísticos
Demanda independiente
Stock de seguridad
Métodos de pronóstico
Costo total del inventario
Dispersión de la demanda
Rights
openAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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dc.title.spa.fl_str_mv An optimization approach for inventory costs in probabilistic inventory models: A case study
dc.title.translated.spa.fl_str_mv Un enfoque de optimización para costos de inventario en modelos de inventario probabilísticos: Un caso de estudio
title An optimization approach for inventory costs in probabilistic inventory models: A case study
spellingShingle An optimization approach for inventory costs in probabilistic inventory models: A case study
Probabilistic inventory models
Independent demand
Safety stock
Forecasting methods
Total cost of inventory
Dispersion of demand
Modelos de inventario probabilísticos
Demanda independiente
Stock de seguridad
Métodos de pronóstico
Costo total del inventario
Dispersión de la demanda
title_short An optimization approach for inventory costs in probabilistic inventory models: A case study
title_full An optimization approach for inventory costs in probabilistic inventory models: A case study
title_fullStr An optimization approach for inventory costs in probabilistic inventory models: A case study
title_full_unstemmed An optimization approach for inventory costs in probabilistic inventory models: A case study
title_sort An optimization approach for inventory costs in probabilistic inventory models: A case study
dc.creator.fl_str_mv Pulido-Rojano, Alexander
Andrea, Andrea
Padilla-Polanco, Miguel
Sánchez-Jiménez, Milton
De la-Rosa, Ladianys
dc.contributor.author.none.fl_str_mv Pulido-Rojano, Alexander
Andrea, Andrea
Padilla-Polanco, Miguel
Sánchez-Jiménez, Milton
De la-Rosa, Ladianys
dc.subject.eng.fl_str_mv Probabilistic inventory models
Independent demand
Safety stock
Forecasting methods
Total cost of inventory
Dispersion of demand
topic Probabilistic inventory models
Independent demand
Safety stock
Forecasting methods
Total cost of inventory
Dispersion of demand
Modelos de inventario probabilísticos
Demanda independiente
Stock de seguridad
Métodos de pronóstico
Costo total del inventario
Dispersión de la demanda
dc.subject.spa.fl_str_mv Modelos de inventario probabilísticos
Demanda independiente
Stock de seguridad
Métodos de pronóstico
Costo total del inventario
Dispersión de la demanda
description Inventories represent stocks of goods necessary for operations of sales or manufacturing in a company. These allow to the companies meet their sales levels, while representing an opportunity to the cost control and the decision-making. This paper presents an optimization approach to minimize the inventory costs in probabilistic inventory models of independent demand. The approach has been validated for set the policy optimal of inventories with probabilistic demand within a company that markets disposable products. The established policy aims to minimize the inventory costs by using the standard deviation of the historical data, the mean deviation of forecast errors and the mean deviation of the historical data. For the determination of the economic order quantities, three types of products were selected, taking historical sales data. Likewise, different forecasting methods were used, selecting the one that minimizes the mean squared error for the forecasted demand. The proposed methodology is practical and easy to use in companies where inventories have probabilistic and independent demand. Also, the proposed approach allowed optimize the costs related to holding costs, ordering costs and safety stock costs.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-10-02T16:17:55Z
dc.date.available.none.fl_str_mv 2020-10-02T16:17:55Z
dc.date.issued.none.fl_str_mv 2020
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dc.type.spa.spa.fl_str_mv Artículo científico
dc.identifier.issn.none.fl_str_mv 07183305
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12442/6620
dc.identifier.url.none.fl_str_mv https://www.ingeniare.cl/index.php?option=com_ingeniare&view=d&doc=106/03-_PULIDO-ROJANO-28-3_ultima_version.pdf&aid=799&vid=106&lang=es
identifier_str_mv 07183305
url https://hdl.handle.net/20.500.12442/6620
https://www.ingeniare.cl/index.php?option=com_ingeniare&view=d&doc=106/03-_PULIDO-ROJANO-28-3_ultima_version.pdf&aid=799&vid=106&lang=es
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv pdf
dc.publisher.spa.fl_str_mv Universidad de Tarapacá
dc.source.spa.fl_str_mv Ingeniare. Revista chilena de ingeniería
Vol. 28 Nº 3, (2020)
institution Universidad Simón Bolívar
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spelling Pulido-Rojano, Alexander032b0909-cceb-4be6-81e5-905767bf8313Andrea, Andrea8f693572-da6c-4690-a4b4-bd775af17a37Padilla-Polanco, Miguel3980c508-afdd-437e-b105-741fa51cfaceSánchez-Jiménez, Miltonc29cd9b0-3beb-4cd7-b052-afdd305a7939De la-Rosa, Ladianys6f9e130d-8272-483b-85d5-f4543a3c8b562020-10-02T16:17:55Z2020-10-02T16:17:55Z202007183305https://hdl.handle.net/20.500.12442/6620https://www.ingeniare.cl/index.php?option=com_ingeniare&view=d&doc=106/03-_PULIDO-ROJANO-28-3_ultima_version.pdf&aid=799&vid=106&lang=esInventories represent stocks of goods necessary for operations of sales or manufacturing in a company. These allow to the companies meet their sales levels, while representing an opportunity to the cost control and the decision-making. This paper presents an optimization approach to minimize the inventory costs in probabilistic inventory models of independent demand. The approach has been validated for set the policy optimal of inventories with probabilistic demand within a company that markets disposable products. The established policy aims to minimize the inventory costs by using the standard deviation of the historical data, the mean deviation of forecast errors and the mean deviation of the historical data. For the determination of the economic order quantities, three types of products were selected, taking historical sales data. Likewise, different forecasting methods were used, selecting the one that minimizes the mean squared error for the forecasted demand. The proposed methodology is practical and easy to use in companies where inventories have probabilistic and independent demand. Also, the proposed approach allowed optimize the costs related to holding costs, ordering costs and safety stock costs.Los inventarios representan la existencia de mercancías necesarias para las operaciones de ventas o fabricación en una empresa. Estos permiten a las empresas cumplir con sus niveles de ventas, al tiempo que representan una oportunidad para el control de costos y la toma de decisiones. Este documento presenta un enfoque de optimización para minimizar los costos de inventario en modelos de inventario probabilísticos de demanda independiente. El enfoque ha sido validado para establecer la política óptima de inventarios con demanda probabilística dentro de una empresa que comercializa productos desechables. La política establecida tiene como objetivo minimizar los costos de inventario utilizando la desviación estándar de los datos históricos, la desviación media de los errores de pronóstico y la desviación media de los datos históricos. Para la determinación de la cantidad económico de pedido, se seleccionaron tres tipos de productos tomando datos históricos de ventas. Asimismo, se utilizaron diferentes métodos de pronóstico, seleccionando el que minimiza el error cuadrático medio para la demanda pronosticada. La metodología propuesta es práctica y de fácil uso en empresas donde los inventarios tienen una demanda probabilística e independiente. Además, el enfoque propuesto permitió optimizar los costos relacionados con los costos de mantenimiento, los costos de pedido y los costos de inventario de seguridad.pdfengUniversidad de TarapacáAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ingeniare. Revista chilena de ingenieríaVol. 28 Nº 3, (2020)Probabilistic inventory modelsIndependent demandSafety stockForecasting methodsTotal cost of inventoryDispersion of demandModelos de inventario probabilísticosDemanda independienteStock de seguridadMétodos de pronósticoCosto total del inventarioDispersión de la demandaAn optimization approach for inventory costs in probabilistic inventory models: A case studyUn enfoque de optimización para costos de inventario en modelos de inventario probabilísticos: Un caso de estudioinfo:eu-repo/semantics/articleArtículo científicohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1A. Pulido-Rojano, A. Villanueva-Polanco, E. Orozco-Acosta y A. Sierra-Altamiranda. “Modelo matemático para la minimización de la escasez de inventarios en cadenas de suministro inestables” (In Spanish). IV Encuentro Iberoamericano de Investigación Operativa y Ciencias Administrativas (IOCA). Santa Cruz de la Sierra, Bolivia. April, 2013.K. Salas-Navarro, H. Maiguel-Mejía y J. Acevedo-Chedid. “Metodología de Gestión de Inventarios para determinar los niveles de integración y colaboración en una cadena de suministro” (In spanish). Ingeniare. Revista Chilena de Ingeniería. Vol. 25 Nº 2, pp. 326- 337. 2017. ISSN: 0718-3291.A. Pulido-Rojano, J. Daza-Escorcia y F. Narducci-Marin. “Modelo analítico de puntos de reorden con demanda dinámica en el tiempo” (In spanish). XIV Congreso latino iberoamericano de investigación de operaciones (CLAIO). Cartagena, Colombia. September, 2008.M. Torres Salazar y P. García Mancera. “Administración de inventarios un desafío para las pymes” (In spanish). Inventio. Vol. 13 Nº 29, pp. 31-38. 2017. ISSN: 2007-1760.M. Arias-Vargas. “Impacto en el inventario de seguridad por la utilización de la desviación estándar de los errores de pronóstico” (In spanish). Tecnología en marcha. Vol. 30 Nº 1, pp. 49-54. 2017. DOI: 10.18845/ tm.v30i1.3064F.A. Nava. “Procesamiento de series de tiempo”. Ediciones Científicas Universitarias. México. 2013. ISBN13: 9786071613509.J.C. Garcia-Diaz. “Predicción en el dominio del tiempo. Análisis de series temporales para ingenieros” (In spanish). Universitat Politècnica de València. Valencia, España. 2016. ISBN: 978-84-9048-438-8.A. Pulido-Rojano, P. Sanchez-Sanchez, y E. Melamed-Varela. “Nuevas tendencias en Investigación de Operaciones y Ciencias Administrativas: Un enfoque desde estudios iberoamericanos” (In spanish). Ediciones Universidad Simón Bolívar. Barranquilla, Colombia. 2018. ISBN: 978-958-5430-88-4P. Sanchez-Sanchez, J.R. García-González, C.H. Fajardo Toro, A. Pulido-Rojano, y E. Melamed-Varela. “Simulación de sistemas de emergencia en salud” (In spanish). En: A. Pulido-Rojano, P. Sanchez-Sanchez, y E. Melamed-Varela. (eds.). Nuevas tendencias en investigación de operaciones y ciencias administrativas: Un enfoque desde estudios iberoamericanos, pp. 165-210. Ediciones Universidad Simón Bolívar. Barranquilla, Colombia. 2018.P. Riquelme, G. Gatica y E. Orozco. “Diseño de un Modelo de Operación para Ruteo de Transporte Urbano Basado en Simulación Discreta” (In spanish). Investigación e Innovación en Ingenierías. Vol. 3 Nº 2. 2015. URL: https://doi.org/10.17081/ invinno.3.2.2026.R. Álvarez Martínez, V. Ávila Díaz y J. Castañeda Villacob. “Herramientas para la gestión de la productividad en la empresa: Experiencias exitosas desde el Caribe colombiano” (In spanish). Ediciones Universidad Simón Bolívar. Barranquilla, Colombia. 2017.H. Taha. “Operations Research: An Introduction”. Pearson. 10 edition. New York, United States. 2016. ISBN: 978-0134444017.D.R. Anderson, D.J. Sweeney, T.A. Williams, J.D. Camm, J.J. Cochran and M.J. Fry. “Quantitative Methods for Business”. Cengage Learning. 13 edition. Boston, United States. 2015. ISBN: 9781285866314.Y. Zhang, G. Hua, S. Wang, J. Zhang and V. Fernandez. “Managing demand uncertainty: Probabilistic selling versus inventory substitution”. International Journal of Production Economics. Vol. 196 (C), pp. 56-67. 2018. ISSN: 0925-5273. DOI: 10.1016/j.ijpe.2017.10.001A. Nodari, J.K. Nurminen and C. Frühwirth. “Inventory theory applied to cost optimization in cloud computing”. Proceedings of the 31st Annual ACM Symposium on Applied Computing (SAC16), pp. 470- 473. April, 2016. URL: http://dx.doi. org/10.1145/2851613.2851869M. Reza, K. Behrooz and F.G. Seyyed Mohammad. “Effect of two-echelon trade credit on pricing-inventory policy of noninstantaneous deteriorating products with probabilistic demand and deterioration functions”. Annals of Operations Research. Vol. 257, pp. 237-273. 2017. ISSN: 0254-5330A.A. Taleizadeh, H. Reza Zarei and B.R. Sarker. “An optimal control of inventory under probablistic replenishment intervals and known price increase”. European Journal of Operational Research. Vol. 257, Issue 3, pp. 777-791. 2017. ISSN: 0377-2217. URL: https://doi.org/10.1016/j.ejor.2016.07.041S. Priyan and R. Uthayakumar. “An integrated production-distribution inventory system involving probabilistic defective and errors in quality inspection under variable setup cost”. International Transactions in Operational Research. Vol. 24, Issue 6, pp. 1487-1524. 2017. ISSN: 1475-3995. URL: https://doi. org/10.1111/itor.12202H. Mokhtari. “Economic order quantity for joint complementary and substitutable items”. Mathematics and Computers in Simulation. Vol. 154, pp. 34-47. 2018. ISSN: 03784754. DOI: 10.1016/j.matcom.2018.06.004L.A. San-José, J. Sicilia, M. González-de-laRosa and J. Febles-Acosta. “An economic order quantity model with nonlinear holding cost, partial backlogging and ramp-type demand”. Engineering Optimization. Vol. 50, Issue 7, pp. 1164-1177. 2018. ISSN: 0305215X. DOI: 10.1080/0305215X.2017.1414205K. Skouri. “An EOQ model with backlogdependent demand”. Operational Research. Vol. 18, Issue 2, pp. 561-574. 2018. ISSN: 11092858. DOI: 10.1007/s12351-016-0279-0.I. Krommyda, K. Skouri and A.G. Lagodimos. “A unified EOQ model with financial constraints and market tolerance”. Applied Mathematical Modelling. Vol. 65, Issue 1, pp. 89-105. 2019. ISSN: 0307904X. DOI: 10.1016/j.apm.2018.08.002J. Huang. “Improvement of inventory control and forecast according to activity-based classifications: T company as an example”. WSEAS Transactions on Business and Economics. Vol. 14, pp. 38-54. 2017. ISSN: 11099526.R. Hyndman and G. Athanasopoulos. “Forecasting: principles and practice” 2nd edition. OTexts. Melbourne, Australia. 2018B. Billah, M.L. King, R.D. Snyder and A.B. Koehler. “Exponential smoothing model selection for forecasting”. International Journal of Forecasting. Vol. 22, Issue 2. pp. 239-247. 2006. 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