Publicado

2018-04-01

Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions

Comparación de tres modelos basados en el IRP para reducir costos logísticos y emisiones de gases efecto invernadero

DOI:

https://doi.org/10.15446/dyna.v85n205.68282

Palabras clave:

goods distribution, multiobjective model, collaborative inventory, Greenhouse Gases (en)
distribución de mercancías, modelo multiobjetivo, inventario colaborativo, Gases de efecto invernadero (es)

Descargas

Autores/as

Goods distribution processes must reconcile the economic interests of the companies, which seek higher levels of profitability through costs reduction and service level improvements, with the negative impacts to society and environment, such as chemical pollution and the generation of vehicular congestion and accidents. This article presents the comparison of three models that analyze the logistics costs associated with the distribution of goods and the greenhouse gas emissions generated by such processes. These models use the Vehicle Routing Problem (IRP) as the basis for optimizing the logistics activities, from which, through multi-objective approaches the CO2 emissions are analyzed. As the main result of the article, it can be observed that the multiobjective models allow finding an adequate combination between logistics costs and emissions, which is attractive to companies and society.

Los procesos de distribución de mercancías deben conciliar los intereses económicos de las empresas, que buscan mayores niveles de rentabilidad a través de disminución de los costos y mejoras del nivel de servicio, con los impactos negativos que se producen a la sociedad y al medio ambiente, como es el caso de la contaminación química y problemas de calidad de vida, como la generación de congestión vehicular y accidentes. En este articulo se presenta la comparación de tres modelos que analizan los costos logísticos asociados a la distribución de mercancías y las emisiones de gases efecto invernado que generan dicho procesos. Estos modelos utilizan el Problema de Ruteo de Vehículos (IRP) como base para optimizar las actividades logísticas, a partir del cual, mediante enfoques multobjetivo se analizan las emisiones de CO2. Como principal resultado del articulo se observa que los modelos multiobjetivo permiten encontrar una combinación adecuada entre los costos logísticos y las emisiones, que sea atractivo para empresas y la sociedad.

Referencias

Chan, F.T.S. and Prakash, A., Inventory management in a lateral collaborative manufacturing supply chain: a simulation study. International Journal of production Research, 50(16), pp. 4670-4685, 2012.

Simatupang, T. and Sridharan, R., An integrative framework for supply chain collaboration. International Journal of Logistics Management, 16, pp. 257-274, 2005.

Arango-Serna, M.D., Adarme-Jaimes, W. y Zapata-Cortes, J.A., Inventarios colaborativos en la optimización de la cadena de suministros. DYNA, 80(181), pp. 71-80, 2013.

Holweg, M., Disney, S., Holmström, J. and Smaros, J., Supply chain collaboration: making sense of the strategy continuum. European Management Journal, 23(2), pp. 170-181, 2005.

Derroiche, R., Neubert, G. and Bouras, A., Supply chain management: a framework to characterize the collaborative strategies. International Journal of Computer Integrated Manufacturing, 21(4), pp. 426-439, 2008.

Díaz-Batista, J. and Pérez-Armayor, D., Optimización de los niveles de inventario en una cadena de suministro. Ingeniería Industrial, 33(2), pp. 126-132, 2012.

Won-Cho, D., Hae-Lee, Y., Youn-Lee, T. and Gen, M., An adaptive genetic algorithm for the time dependent inventory routing problem. Journal of Intelligent Manufacturing, 25(5), pp 1025-1042, 2014.

Bertazzi, L. and Esperanza, M.G., Inventory routing problems with multiple customers. EURO J Transp Logist 2. pp 255-275, 2013.

Moin, N.H., Salhi, S. and Aziz, N.A.B., An efficient hybrid genetic algorithm for the multi-product multi-period inventory routing problem. Int. J. Production Economics, 133 pp. 334-343, 2011.

Rushton, P. Croucher, P. and Baker, P., The handbook of logistics and distribution management, 3rd edition. London, Ed. Kogan Page Limited, 2010.

Estrada, M.A., Análisis de estrategias eficientes en la logística de distribución de paquetería. PhD. Thesis, Programa de Doctorado de Ingeniería Civil, E.T.S. de Ingenieros de Caminos, Canales y Puertos de Barcelona, Universitat Politècnica de Catalunya, España, 2007.

Arango, M.D., Zapata, J.A. y Adarme, W., Aplicación del modelo de inventario manejado por el vendedor en una empresa del sector alimentario colombiano, Revista EIA, 15, pp. 21-32, 2011.

Gonzalez-Feliu, J., Peris-Pla, C. and Rakotonarivo, D., Simulation and optimization methods for logistics pooling in the outbound supply chain. Third International Conference on Value Chain Sustainability, Towards a Sustainable Development and Corporate Social Re- sponsibility Strategies in the 21st Century Global Market, Nov 2010, Spain, pp. 394-401, 2010.

Arango, M.D. and Zapata, J.A., Multiobjective model for the simultaneous optimization of transportation costs, inventory costs and service level in goods distribution, IEEE Latin America Transactions,. 15(1), Jan. 2017 pp. 129-136, 2017.

Arango, M.D., Zapata, J.A. and Gutierrez, D., Modeling the inventory routing problem (IRP) with multiple depots with genetic algorithms, IEEE Latin American Transactions., 13(12), pp.3959-3965, 2015.

Archetti, C., Bertazzi, L., Laporte, G. and Speranza, M.G., A branch-and- cut algorithm for a vendor-managed inventory-routing problem, Transportation Science, 41(3), pp. 382-391, 2007.

Coelho, L.C., Cordeau, J-F. and Laporte, G., Thirty years of inventory-routing, Transportation Science, 48, pp. 1-19, 2013.

Coelho, L.C. and Laporte, G., The exact solution of several classes of inventory-routing problems, Computers & Operations Research, 40(2013), pp. 558-565, 2013.

Archetti, C., Bianchessi, N., Irnich, S. and Speranza, M.G., Formulations for an inventory routing problem, Intl. Trans. in Op. Res. 21, pp. 353-374, 2014.

Zeng, Z. and Zhao, J., Study of stochastic demand inventory routing problem with soft time windows based on MDP. In: Zeng, Z., Wang, J., (eds), Advances in neural network research and applications. Lecture Notes in Electrical Engineering, 67. Springer, Berlin, Heidelberg, pp. 193-200, 2010.

Arango-Serna, M.D, Andrés-Romano, C. and Zapata-Cortés, J.A., Collaborative goods distribution using the IRP model, DYNA, 83(196), pp. 204-2012, 2016.

Campbell, A. and Savelsbergh, M.A., Decomposition approach for the inventory-routing problem. Transportation Science 38(4), pp. 488-502, 2004.

Seferlis, P. and Pechlivanos, L., Optimal inventory and pricing policies for supply chain networks. European Symposiumon Computer-Aided Process Engineering- 14, 2004.

Chen, C.L. and Lee, W.C., Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices, Computers and Chemical Engineering 28, pp. 1131-1144, 2004.

Liang, T.F., Fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain, Computers & Industrial Engineering, 55, pp. 676-694, 2008.

Liao, H-S., Hsieh, C-H. and Lai, P-G., An evolutionary approach for multi-objective optimization of the integrated location-inventory distribution network problem in vendor-managed inventory, Expert Systems with Applications 38, pp. 6768-6776, 2011.

Afshari, M., Sharafi, T., ElMekkawy, T. and Peng, Q., Optimizing multi- objective dynamic facility location decisions within green distribution network design. Procedia CIRP 17, pp. 675-679, 2014.

Shankar, B.L., Basavarajappa, S., Kadadevaramath, R.S. and Chen, J.C.H., A bi-objective optimization of supply chain design and distribution operations using non-dominated sorting algorithm: A case study, Expert Systems with Applications, 40, pp. 5730-5739, 2013.

Nekooghadirli, N., Tavakkoli-Moghaddam, R., Ghezavati, V.R. and Javanmard, S., Solving a new bi-objective location-routing-inventory problem in a distribution network by meta-heuristics, Computers & Industrial Engineering, 76, pp. 204-221, 2014.

Andriolo, A., Battini, D., Persona, A. and Sgarbossa, F., Haulage sharing approach to achieve sustainability in material purchasing: new method and numerical applications, Int. J. Production Economics, 164, pp. 308-318, 2015.

Pasandideh, S.H.R., Niaki, S.T.A. and Asadi, K., Optimizing a bi- objective multi-product multi-period three echelon supply chain network with warehouse reliability, Expert Systems with Applications, 42, pp. 2615-2623, 2015.

Pasandideh, S.H.R., Niaki, S.T.A. and Asadi, K., Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: NSGA-II and NRGA, Information Sciences, 292, pp. 57-74, 2015.

Arango, M.D., Zapata, J.A. and Andres, C., Metaheuristics for goods distribution. Proceedings of 2015 International Conference on Industrial Engineering and Systems Management (IESM), IEEE Publications, pp. 99-107, 2015. DOI. 10.1109/IESM.2015.7380143, 2015.

Villalobos, M.A., Análisis de heurísticas de optimización para problemas multiobjetivo. PhD. Thesis, Departamento de Matemáticas. Centro de investigación y de estudios avanzados del Instituto Politécnico Nacional, Mexico, 2005.

López, J., Zapotecas, S. and Coello, C.A., An introduction to multiobjective optimization techniques. In: Ajith, A., Lakhmi, J. and Goldberg, R. (eds)., Evolutionary multiobjective optimization: theoretical advances and applications, London, Springer-Verlag, pp. 7-32, 2009.

González-Álvarez, D., Optimización multiobjetivo y paralelismo para descubrir Motifs en secuencias de ADN, PhD. Thesis, Universidad de Extremadura, Extremadura, España, 2013.

Zapata-Cortes, J.A., Optimización de la distribución de mercancías utilizando un modelo genético multiobjetivo de inventario colaborativo de m proveedores con n clientes, PhD. Thesis, Universidad Nacional de Colombia, Medellín, [en línea]. 2016. Disponible en: www.bdigital.unal.edu.co/53703/1/71366786. 2016.pdf, 2016

Arango-Serna, M.D., Zapata-Cortes, J.A. and Serna-Uran, C.A., Collaborative multiobjective model for urban goods distribution optimization, in: García-Alcaraz, J., Alor-Hernández, G., Maldonado-Macías, A., Sánchez-Ramírez, C. (eds), New perspectives on applied industrial tools and techniques. Management and Industrial Engineering. Springer, Cham, 2018.

Ford Motor Company. Ford Transit, [online]. [Date of reference: April of 2016]. 2016. Available at: http://es.ford.com/trucks/ transitvanwagon/specifications/

Cómo citar

IEEE

[1]
J. A. Zapata-Cortes, M. D. Arango-Serna, y C. A. Serna Uran, «Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions», DYNA, vol. 85, n.º 205, pp. 199–204, abr. 2018.

ACM

[1]
Zapata-Cortes, J.A., Arango-Serna, M.D. y Serna Uran, C.A. 2018. Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions. DYNA. 85, 205 (abr. 2018), 199–204. DOI:https://doi.org/10.15446/dyna.v85n205.68282.

ACS

(1)
Zapata-Cortes, J. A.; Arango-Serna, M. D.; Serna Uran, C. A. Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions. DYNA 2018, 85, 199-204.

APA

Zapata-Cortes, J. A., Arango-Serna, M. D., & Serna Uran, C. A. (2018). Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions. DYNA, 85(205), 199–204. https://doi.org/10.15446/dyna.v85n205.68282

ABNT

ZAPATA-CORTES, J. A.; ARANGO-SERNA, M. D.; SERNA URAN, C. A. Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions. DYNA, [S. l.], v. 85, n. 205, p. 199–204, 2018. DOI: 10.15446/dyna.v85n205.68282. Disponível em: https://revistas.unal.edu.co/index.php/dyna/article/view/68282. Acesso em: 8 ago. 2022.

Chicago

Zapata-Cortes, Julian Andres, Martín Dario Arango-Serna, y Conrado Augusto Serna Uran. 2018. «Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions». DYNA 85 (205):199-204. https://doi.org/10.15446/dyna.v85n205.68282.

Harvard

Zapata-Cortes, J. A., Arango-Serna, M. D. y Serna Uran, C. A. (2018) «Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions», DYNA, 85(205), pp. 199–204. doi: 10.15446/dyna.v85n205.68282.

MLA

Zapata-Cortes, J. A., M. D. Arango-Serna, y C. A. Serna Uran. «Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions». DYNA, vol. 85, n.º 205, abril de 2018, pp. 199-04, doi:10.15446/dyna.v85n205.68282.

Turabian

Zapata-Cortes, Julian Andres, Martín Dario Arango-Serna, y Conrado Augusto Serna Uran. «Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions». DYNA 85, no. 205 (abril 1, 2018): 199–204. Accedido agosto 8, 2022. https://revistas.unal.edu.co/index.php/dyna/article/view/68282.

Vancouver

1.
Zapata-Cortes JA, Arango-Serna MD, Serna Uran CA. Comparisson of three IRP-based models to reduce logistics costs and greenhouse gas emissions. DYNA [Internet]. 1 de abril de 2018 [citado 8 de agosto de 2022];85(205):199-204. Disponible en: https://revistas.unal.edu.co/index.php/dyna/article/view/68282

Descargar cita

Dimensions

PlumX

Descargas

Los datos de descargas todavía no están disponibles.

Visitas a la página del resumen del artículo

438