Long‐term effects of short planning horizons for inventory routing problems

This paper presents a detailed study concerning the importance of the planning horizon when solving inventory routing problems (IRPs). We evaluate the quality of decisions obtained by solving a finite-horizon IRP. We also discuss the relevance of explicitly considering profit maximization models rather than the traditional cost minimization variant. As a means to this end, we describe four classes of the IRP corresponding to different types of markets. Two of them lead to nonlinear models, which are linearized. Furthermore, we provide a deterministic simulator to evaluate the long-term effects arising from using planning horizons of varying lengths when solving the IRP. A computational study is performed on cases generated from benchmark data instances. The results confirm that the long-term performance of the IRP decisions is, in part, contingent on the length of the selected planning horizon. They also show that considering profit maximization instead of cost minimization leads to different decisions, generating considerably more revenue and profits, albeit not nearly as much as suggested by individual solutions to static IRPs with short planning horizons. Keywords: profit maximization, path flow, linearization, end effect, simulationpublishedVersio

Inventory Routing Problem in Perishable Supply Chains: A Literature Review

Context: This paper presents a literature review of the Inventories Routing Problem (IRP) applied to supply chains of perishable products. Different approaches to solve this problem are identified and described in terms of structures, models and solution methods.  Method: A systematic literature review is conducted searching in different bibliographic databases and selecting the most relevant studies within the period 2004 to 2017. The results are analyzed so as to propose a taxonomy to classify and compare the different approaches proposed to address this problem. Results: We identified that the majority of studies consider heuristic-based algorithms to solve the problem. Because of its computational complexity the methods resort to metaheuristics and mateheuristics combined with exact methods. Regarding the application to specific supply chains of perishable products, they refer mostly to processed foods, medicines, and human blood. The constraints that differentiate this problem from other types of IRP are useful life and deterioration. Conclusions: The conditions and particularities of the supply chain of perishables products imply the need to consider new variables, parameters, constraints and objective functions; in the reviewed studies it is not clearly defined the differences involved when considering the perishability of the products in the supply chain. Future research should take into account the multiple ways in which deterioration is carried out with factors such as temperature, light, oxygen, humidity and in some cases microorganisms. Also include in the models the cold chain, hygiene standards, air pollution, emissions of greenhouse gases, generation of waste, occupation of roads and other aspects related to City Logistics and Green Logistics

El Problema de Ruteo e Inventarios en Cadenas de Suministro de Perecederos: Revisión de Literatura

Context: This paper presents a literature review of the Inventories Routing Problem (IRP) applied to supply chains of perishable products. Different approaches to solve this problem are identified and described in terms of structures, models and solution methods. Method: A systematic literature review is conducted searching in different bibliographic databases and selecting the most relevant studies within the period 2004 to 2017. The results are analyzed so as to propose a taxonomy to classify and compare the different approaches proposed to address this problem.Results: We identified that the majority of studies consider heuristic-based algorithms to solve the problem. Because of its computational complexity the methods resort to metaheuristics and mateheuristics combined with exact methods. Regarding the application to specific supply chains of perishable products, they refer mostly to processed foods, medicines, and human blood. The constraints that differentiate this problem from other types of IRP are useful life and deterioration.Conclusions: The conditions and particularities of the supply chain of perishables products imply the need to consider new variables, parameters, constraints and objective functions; in the reviewed studies it is not clearly defined the differences involved when considering the perishability of the products in the supply chain. Future research should take into account the multiple ways in which deterioration is carried out with factors such as temperature, light, oxygen, humidity and in some cases microorganisms. Also include in the models the cold chain, hygiene standards, air pollution, emissions of greenhouse gases, generation of waste, occupation of roads and other aspects related to City Logistics and Green Logistics. Contexto: Revisión de literatura del problema de ruteo e inventarios (IRP) aplicado a las cadenas de suministro de productos perecederos. Se identifican y describen los diferentes enfoques en cuanto a estructuras, modelos y métodos de solución.Método: Se realiza una revisión sistemática de la literatura en diferentes bases de datos bibliográficas y se plantea una taxonomía que clasifica las características de los estudios, lo anterior durante el período comprendido entre 2004 y 2017Resultados: Se encuentra que la mayoría de algoritmos propuestos son de carácter heurístico. Debido a complejidad computacional inherente al problema, se usan metaheurísticas y mateheurísticas combinadas con métodos exactos. Se aplican principalmente en alimentos, medicamentos y sangre humana. Las restricciones que diferencian de otros tipos de IRP son las de periodo de vida útil y deterioro.Conclusiones: Las condiciones y particularidades de la cadena de suministro de perecederos hace necesario que se planteen nuevas variables, parámetros, restricciones y funciones objetivo; por otro lado, en los estudios revisados no se establecen diferencias claras al involucrar la perecibilidad de los productos en los modelos. Las futuras investigaciones deberán tener en cuenta las múltiples maneras en las cuales se lleva a cabo el deterioro con factores como la temperatura, la luz, el oxígeno, la humedad y en algunos casos los microorganismos; asimismo, incluir en los modelos la cadena de frío, normas de higiene, contaminación del aire, emisiones de gases de efecto invernadero, generación de residuos, ocupación de vías y demás aspectos relacionados con city logistics y green logistics.

Redesigning the in-plant supply logistics: A case study

[EN] This paper addresses the redesign of an industrial assembly facility's internal logistics. To this end, it proposes a mathematical formulation that optimizes the components and parts' flow to feed the different workstations of the production lines. This flow of components starts at the reception docks where suppliers' trucks arrive. Components unloaded from trucks are moved to one or several storage areas by means of adequate handling equipment. Finally, components are transported to demand point located along the assembly line when required. Numerical results produced by the mathematical formulation for the studied plant show that savings of almost 33% in the total distribution time might be achieved by a better assignment of suppliers to reception docks and parts to storage areas, and by adequately choosing the capacity of the material handling equipment.The work described in this paper has been partially supported by the project "Hiperheuristico Lenitivo de la Variabilidad del Entorno Industrial en la Programacion de Produccion del Lote Econonimo GVA/2017/008" by the Conselleria de Educacion, Investigacion, Cultura y Deporte of the Generalitat Valenciana within the Program "Proyectos de I+D+I para grupos de investigacion emergentes". We would like to thank the two anonymous reviewers and the editor for their valuable comments and suggestions.Saez-Mas, A.; García Sabater, JP.; García Sabater, JJ.; Ruiz, A. (2020). Redesigning the in-plant supply logistics: A case study. Computers & Industrial Engineering. 143:1-10. https://doi.org/10.1016/j.cie.2020.106422S110143Alizon, F., Dallery, Y., Essafi, I., & Feillet, D. (2009). Optimising material handling costs in an assembly workshop. International Journal of Production Research, 47(14), 3853-3866. doi:10.1080/00207540701851764Alnahhal, M., & Noche, B. (2013). Efficient material flow in mixed model assembly lines. SpringerPlus, 2(1). doi:10.1186/2193-1801-2-415Alnahhal, M., & Noche, B. (2015). A genetic algorithm for supermarket location problem. Assembly Automation, 35(1), 122-127. doi:10.1108/aa-02-2014-018Alnahhal, M., & Noche, B. (2015). Dynamic material flow control in mixed model assembly lines. Computers & Industrial Engineering, 85, 110-119. doi:10.1016/j.cie.2015.03.009Arifin, R., & Egbelu, P. J. (2000). Determination of vehicle requirements in automated guided vehicle systems: A statistical approach. Production Planning & Control, 11(3), 258-270. doi:10.1080/095372800232225Bányai, T. (2018). Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions. Energies, 11(7), 1833. doi:10.3390/en11071833Battini, D., Boysen, N., & Emde, S. (2012). Just-in-Time supermarkets for part supply in the automobile industry. Journal of Management Control, 24(2), 209-217. doi:10.1007/s00187-012-0154-yBattini, D., Gamberi, M., Persona, A., & Sgarbossa, F. (2015). Part-feeding with supermarket in assembly systems: transportation mode selection model and multi-scenario analysis. Assembly Automation, 35(1), 149-159. doi:10.1108/aa-06-2014-053Battini, D., Calzavara, M., Otto, A., & Sgarbossa, F. (2017). Preventing ergonomic risks with integrated planning on assembly line balancing and parts feeding. International Journal of Production Research, 55(24), 7452-7472. doi:10.1080/00207543.2017.1363427Battini, D., Faccio, M., Persona, A., & Sgarbossa, F. (2010). «Supermarket warehouses»: stocking policies optimization in an assembly-to-order environment. The International Journal of Advanced Manufacturing Technology, 50(5-8), 775-788. doi:10.1007/s00170-010-2555-0Boudella, M. E. A., Sahin, E., & Dallery, Y. (2018). Kitting optimisation in Just-in-Time mixed-model assembly lines: assigning parts to pickers in a hybrid robot–operator kitting system. International Journal of Production Research, 56(16), 5475-5494. doi:10.1080/00207543.2017.1418988Boysen, N., Emde, S., Hoeck, M., & Kauderer, M. (2015). Part logistics in the automotive industry: Decision problems, literature review and research agenda. European Journal of Operational Research, 242(1), 107-120. doi:10.1016/j.ejor.2014.09.065Boywitz, D., Boysen, N., & Briskorn, D. (2016). Resequencing with parallel queues to minimize the maximum number of items in the overflow area. Naval Research Logistics (NRL), 63(5), 401-415. doi:10.1002/nav.21699Caputo, A. C., Pelagagge, P. M., & Salini, P. (2017). Modeling errors in parts supply processes for assembly lines feeding. Industrial Management & Data Systems, 117(6), 1263-1294. doi:10.1108/imds-08-2016-0333Caputo, A. C., Pelagagge, P. M., & Salini, P. (2017). Modelling human errors and quality issues in kitting processes for assembly lines feeding. Computers & Industrial Engineering, 111, 492-506. doi:10.1016/j.cie.2017.04.004Carter, C. R., & Rogers, D. S. (2008). A framework of sustainable supply chain management: moving toward new theory. International Journal of Physical Distribution & Logistics Management, 38(5), 360-387. doi:10.1108/09600030810882816Ellis, K. P., Meller, R. D., Wilck, J. H., Parikh, P. J., & Marchand, F. (2010). Effective material flow at an assembly facility. International Journal of Production Research, 48(23), 7195-7217. doi:10.1080/00207540903186266Emde, S., & Boysen, N. (2012). Optimally locating in-house logistics areas to facilitate JIT-supply of mixed-model assembly lines. International Journal of Production Economics, 135(1), 393-402. doi:10.1016/j.ijpe.2011.07.022Emde, S., Fliedner, M., & Boysen, N. (2012). Optimally loading tow trains for just-in-time supply of mixed-model assembly lines. IIE Transactions, 44(2), 121-135. doi:10.1080/0740817x.2011.575442Enderer, F., Contardo, C., & Contreras, I. (2017). Integrating dock-door assignment and vehicle routing with cross-docking. Computers & Operations Research, 88, 30-43. doi:10.1016/j.cor.2017.06.018Cedillo-Campos, M. G., Morones Ruelas, D., Lizarraga-Lizarraga, G., Gonzalez-Feliu, J., & Garza-Reyes, J. A. (2017). Decision policy scenarios for just-in-sequence (JIS) deliveries. Journal of Industrial Engineering and Management, 10(4), 581. doi:10.3926/jiem.2090Golz, J., Gujjula, R., Günther, H.-O., Rinderer, S., & Ziegler, M. (2011). Part feeding at high-variant mixed-model assembly lines. Flexible Services and Manufacturing Journal, 24(2), 119-141. doi:10.1007/s10696-011-9116-1Hernández-Rodríguez, S., Hernández-Lira, C. A., Aguilar-Rico, A., Flores-Becerra, G., Flores-Méndez, J., & Vázquez-Cuchillo, O. (2016). A recommender system applied to the indirect materials selection process (RS-IMSP) for producing automobile spare parts. Computers in Industry, 82, 233-244. doi:10.1016/j.compind.2016.07.004Khajavi, S. H., Baumers, M., Holmström, J., Özcan, E., Atkin, J., Jackson, W., & Li, W. (2018). To kit or not to kit: Analysing the value of model-based kitting for additive manufacturing. Computers in Industry, 98, 100-117. doi:10.1016/j.compind.2018.01.022Korytkowski, P., & Karkoszka, R. (2015). Simulation-based efficiency analysis of an in-plant milk-run operator under disturbances. The International Journal of Advanced Manufacturing Technology, 82(5-8), 827-837. doi:10.1007/s00170-015-7442-2Kozan, E. (2000). An integrated material handling system for a truck assembly plant. Journal of the Operational Research Society, 51(3), 263-271. doi:10.1057/palgrave.jors.2600921Nasiri, M. M., Rahbari, A., Werner, F., & Karimi, R. (2018). Incorporating supplier selection and order allocation into the vehicle routing and multi-cross-dock scheduling problem. International Journal of Production Research, 56(19), 6527-6552. doi:10.1080/00207543.2018.1471241Nourmohammadi, A., & Eskandari, H. (2017). Assembly line design considering line balancing and part feeding. Assembly Automation, 37(1), 135-143. doi:10.1108/aa-09-2016-122Nourmohammadi, A., Eskandari, H., & Fathi, M. (2018). Design of stochastic assembly lines considering line balancing and part feeding with supermarkets. Engineering Optimization, 51(1), 63-83. doi:10.1080/0305215x.2018.1439944Saez-Mas, A., Garcia-Sabater, J. P., & Morant-Llorca, J. (2018). Using 4-Layer Architecture to Simulate Product and Information Flows in Manufacturing Systems. International Journal of Simulation Modelling, 17(1), 30-41. doi:10.2507/ijsimm17(1)408Staab, T., Klenk, E., Galka, S., & Günthner, W. A. (2016). Efficiency in in-plant milk-run systems—The influence of routing strategies on system utilization and process stability. Journal of Simulation, 10(2), 137-143. doi:10.1057/jos.2015.6Wagner, S. M., & Silveira-Camargos, V. (2011). Decision model for the application of just-in-sequence. International Journal of Production Research, 49(19), 5713-5736. doi:10.1080/00207543.2010.505216Wang, C., Guan, Z., Shao, X., & Ullah, S. (2014). Simulation-based optimisation of logistics distribution system for an assembly line with path constraints. International Journal of Production Research, 52(12), 3538-3551. doi:10.1080/00207543.2013.874602Wang, J., Chang, Q., Xiao, G., Wang, N., & Li, S. (2011). Data driven production modeling and simulation of complex automobile general assembly plant. Computers in Industry, 62(7), 765-775. doi:10.1016/j.compind.2011.05.004Wänström, C., & Medbo, L. (2008). The impact of materials feeding design on assembly process performance. Journal of Manufacturing Technology Management, 20(1), 30-51. doi:10.1108/17410380910925398Zangaro, F., Battini, D., Calzavara, M., Persona, A., & Sgarbossa, F. (2018). A Model to Optimize the Reference Storage Assignment in a Supermarket to Expedite the Part Feeding Activities. IFAC-PapersOnLine, 51(11), 1470-1475. doi:10.1016/j.ifacol.2018.08.296Zenker, M., Emde, S., & Boysen, N. (2016). Cyclic inventory routing in a line-shaped network. European Journal of Operational Research, 250(1), 164-178. doi:10.1016/j.ejor.2015.10.067Zhou, B., & Peng, T. (2017). Scheduling the in-house logistics distribution for automotive assembly lines with just-in-time principles. Assembly Automation, 37(1), 51-63. doi:10.1108/aa-04-2016-02