Scheduling unrelated parallel machines with resource-assignable sequence-dependent setup times

[EN] A novel scheduling problem that results from the addition of resource-assignable setups is presented in this paper. We consider an unrelated parallel machine problem with machine and job sequence-dependent setup times. The new characteristic is that the amount of setup time does not only depend on the machine and job sequence but also on the amount of resources assigned, which can vary between a minimum and a maximum. The aim is to give solution to real problems arising in several industries where frequent setup operations in production lines have to be carried out. These operations are indeed setups whose length can be reduced or extended according to the amount of resources assigned to them. The objective function considered is a linear combination of total completion time and the total amount of resources assigned. We present a mixed integer program (MIP) model and some fast dispatching heuristics. We carry out careful and comprehensive statistical analyses to study what characteristics of the problem affect the MIP model performance. We also study the effectiveness of the different heuristics proposed. © 2011 Springer-Verlag London Limited.The authors are indebted to the referees and editor for a close examination of the paper, which has increased its quality and presentation. This work is partially funded by the Spanish Ministry of Science and Innovation, under the project "SMPA-Advanced Parallel Multiobjective Sequencing: Practical and Theoretical Advances" with reference DPI2008-03511/DPI. The authors should also thank the IMPIVA-Institute for the Small and Medium Valencian Enterprise, for the project OSC with references IMIDIC/2008/137, IMIDIC/2009/198, and IMIDIC/2010/175.Ruiz García, R.; Andrés Romano, C. (2011). Scheduling unrelated parallel machines with resource-assignable sequence-dependent setup times. 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Metodologías de formación de familias considerando la minimización de los tiempos de cambio de partida. Aplicación a la secuenciación en empresas cerámicas.

En este artículo se presentan los resultados finales de un estudio realizado sobre la creación defamilias de piezas en empresas del sector cerámico. En este sector, la elevada personalización de los productos demandados por los clientes, ha llevado a la

Aplicación de metodologías de Evaluación ergonómica de puestos de trabajo en la planta de carrocerías de Ford España S.A.

El análisis ergonómico presenta un creciente interés social, tanto por la incidencia que tiene sobre la salud de los trabajadores la falta de adecuación de los puestos de trabajo, como por los logros en la mejora de las condiciones de los mismos que se c

La mejora de la empleabilidad de los discapacitados a través de los Centros de Ocupación laboral. Aportaciones de la Ingeniería de Organización Industrial.

El objetivo de este articulo es presentar un proyecto de investigación que pretende extender los beneficios de las técnicas de Ingeniería de Métodos a los entornos relacionados con los Centros Ocupacionales y Centros Especiales de Empleo de discapacitad

A hybrid approach based on genetic algorithms to solve the problem of cutting structural beams in a metalwork company

This work presents a hybrid approach based on the use of genetic algorithms to solve efficiently the problem of cutting structural beams arising in a local metalwork company. The problem belongs to the class of one-dimensional multiple stock sizes cutting stock problem, namely 1-dimensional multiple stock sizes cutting stock problem. The proposed approach handles overproduction and underproduction of beams and embodies the reusability of remnants in the optimization process. Along with genetic algorithms, the approach incorporates other novel refinement algorithms that are based on different search and clustering strategies.Moreover, a new encoding with a variable number of genes is developed for cutting patterns in order to make possible the application of genetic operators. The approach is experimentally tested on a set of instances similar to those of the local metalwork company. In particular, comparative results show that the proposed approach substantially improves the performance of previous heuristics.Gracia Calandin, CP.; Andrés Romano, C.; Gracia Calandin, LI. (2013). A hybrid approach based on genetic algorithms to solve the problem of cutting structural beams in a metalwork company. Journal of Heuristics. 19(2):253-273. doi:10.1007/s10732-011-9187-xS253273192Aktin, T., Özdemir, R.G.: An integrated approach to the one dimensional cutting stock problem in coronary stent manufacturing. Eur. J. Oper. Res. 196, 737–743 (2009)Alves, C., Valério de Carvalho, J.M.: A stabilized branch-and-price-and-cut algorithm for the multiple length cutting stock problem. Comput. Oper. Res. 35, 1315–1328 (2008)Anand, S., McCord, C., Sharma, R., et al.: An integrated machine vision based system for solving the nonconvex cutting stock problem using genetic algorithms. J. Manuf. Syst. 18, 396–415 (1999)Belov, G., Scheithauer, G.: A cutting plane algorithm for the one-dimensional cutting stock problem with multiple stock lengths. Eur. J. Oper. Res. 141, 274–294 (2002)Christofides, N., Hadjiconstantinou, E.: An exact algorithm for orthogonal 2-D cutting problems using guillotine cuts. Eur. J. Oper. Res. 83, 21–38 (1995)Elizondo, R., Parada, V., Pradenas, L., Artigues, C.: An evolutionary and constructive approach to a crew scheduling problem in underground passenger transport. J. Heuristics 16, 575–591 (2010)Fan, L., Mumford, C.L.: A metaheuristic approach to the urban transit routing problem. J. Heuristics 16, 353–372 (2010)Gau, T., Wäscher, G.: CUTGEN1: a problem generator for the standard one-dimensional cutting stock problem. Eur. J. Oper. Res. 84, 572–579 (1995)Gilmore, P.C., Gomory, R.E.: A linear programming approach to the cutting stock problem. Oper. Res. 9, 849–859 (1961)Gilmore, P.C., Gomory, R.E.: A linear programming approach to the cutting stock problem. Part II. Oper. Res. 11, 863–888 (1963)Ghiani, G., Laganà, G., Laporte, G., Mari, F.: Ant colony optimization for the arc routing problem with intermediate facilities under capacity and length restrictions. J. Heuristics 16, 211–233 (2010)Gonçalves, J.F., Resende, G.C.: Biased random-key genetic algorithms for combinatorial optimization. J. Heuristics (2011). doi: 10.1007/s10732-010-9143-1Gradisar, M., Kljajic, M., Resinovic, G., et al.: A sequential heuristic procedure for one-dimensional cutting. Eur. J. Oper. Res. 114, 557–568 (1999)Haessler, R.W.: One-dimensional cutting stock problems and solution procedures. Math. Comput. Model. 16, 1–8 (1992)Haessler, R.W., Sweeney, P.E.: Cutting stock problems and solution procedures. Eur. J. Oper. Res. 54(2), 141–150 (1991)Haessler, R.W.: Solving the two-stage cutting stock problem. 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Secuenciación con Almacenes Limitados. Una Revisión de la Literatura

[ES] Tradicionalmente, en la aproximación formal a la secuenciación de producción denominada en inglés Theory of Scheduling (o simplemente scheduling), se suele obviar la limitación de capacidad entre los diferentes recursos de cara a establecer el programa de producción. Sin embargo, el paradigma Lean Manufacturing ha dejado patente que la limitación de capacidad física en los sistemas productivos es una característica que influye en los resultados de los programas de producción, por lo que las configuraciones empezando a ser objeto de estudio en la dirección de operaciones. En este artículo se hace una revisión de las principales características de la secuenciación con almacenes limitados que se han abordado bajo la teoría de secuenciación y se resumen las referencias más importantes publicadas durante los últimos años. Finalmente, se presentan una serie de conclusiones con el objetivo de clarificar algunas líneas de interés para los investigadores del tema.Andrés Romano, C.; Maheut, J. (2018). Secuenciación con Almacenes Limitados. Una Revisión de la Literatura. Dirección y organización (Online). 66:17-33. http://hdl.handle.net/10251/145863S17336

A Multi Ant Colony Optimization algorithm for a Mixed Car Assembly Line

This paper presents an ant colony optimization algorithm to sequence the mixed assembly lines considering the inventory and the replenishment of components. This is a NP-problem that cannot be solved to optimality by exact methods when the size of the problem growth. Groups of specialized ants are implemented to solve the different parts of the problem. This is intended to differentiate each part of the problem. Different types of pheromone structures are created to identify good car sequences, and good routes for the replenishment of components vehicle. The contribution of this paper is the collaborative approach of the ACO for the mixed assembly line and the replenishment of components and the jointly solution of the problem

A review of lot streaming in a flow shop environment with makespan criteria

[EN] Purpose: This paper reviews current literature and contributes a set of findings that capture the current state-of-the-art of the topic of lot streaming in a flow-shop. Design/methodology/approach: A literature review to capture, classify and summarize the main body of knowledge on lot streaming in a flow-shop with makespan criteria and, translate this into a form that is readily accessible to researchers and practitioners in the more mainstream production scheduling community. Findings: The existing knowledge base is somewhat fragmented. This is a relatively unexplored topic within mainstream operations management research and one which could provide rich opportunities for further exploration. Originality/value: This paper sets out to review current literature, from an advanced production scheduling perspective, and contributes a set of findings that capture the current state-of-the-art of this topic.This work has been carried out as part of the project “Programación de la Producción con Partición Ajustable de Lotes en entornos de Planificación mixta Pedido/Stock (PP-PAL-PPS)”, ref. GVA/2013/034 funded by Consellería de Educación, Cultura y Deportes de la Generalitat Valenciana.Gómez-Gasquet, P.; Segura Andrés, R.; Andrés Romano, C. (2013). A review of lot streaming in a flow shop environment with makespan criteria. Journal of Industrial Engineering and Management. 6(3):761-770. https://doi.org/10.3926/jiem.553S7617706

Collaborative goods distribution using the IRP model

[EN] This paper presents a study of the impact that collaboration in inventory has on distribution costs in a network of one supplier and multiple customers. Freight transport is widely studied due to its impact on logistics costs and service levels of enterprises. Looking for network configurations that improve some of these aspects will always be attractive to both academics and businesses. The collaborative distribution system was proposed using the IRP model, and it was compared with the scenarios in which the both supplier or customers optimize their inventory levels. For the IRP model solution a genetic algorithm was used, from which it was obtained a collaborative distribution system with a better performance than if the optimization is made independently.[ES] Este artículo presenta un estudio sobre el impacto que tiene la distribución colaborativa sobre los costos en la toma de las decisiones del inventario entre un proveedor y múltiples clientes, utilizando el modelo IRP para definir el sistema de distribución. El transporte de mercancías es una actividad ampliamente estudiada debido al impacto tiene en los costos logísticos y en el nivel de servicio de las empresas. Buscar redes de distribución que mejoren alguno de estos aspectos siempre será atractivo tanto para académicos como para las empresas. El resultado producido por el modelo IRP fue comparado con los escenarios en que el proveedor y los clientes optimizan sus niveles de inventario. Para la solución del modelo IRP se utilizó un algoritmo genético, a partir del cual se logro obtener un sistema de distribución en colaboración con un mejor desempeño que el correspondiente cuando la optimización se hace de forma independienteLos autores agradecen a la Universidad Nacional de Colombia por el apoyo al proyecto Optimización de la distribución de mercancías utilizando un modelo genético multiobjetivo de n proveedores con m clientes , código Hermes: 29314. Proyecto del cual se deriva este artículo de investigación.Arango Serna, MD.; Andrés Romano, C.; Zapata-Cortés, JA. (2016). Distribución colaborativa de mercancías utilizando el modelo IRP. DYNA. 83(196):204-212. https://doi.org/10.15446/dyna.v83n196.52492S2042128319