A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments

The definition of lot sizes represents one of the most important decisions in production planning. Lot-sizing turns into an increasingly complex set of decisions that requires efficient solution approaches, in response to the time-consuming exact methods (LP, MIP). This paper aims to propose a Tabu...

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Autores:: Romero-Conrado, Alfonso R.
Coronado-Hernandez, Jairo R.
Rius-Sorolla, Gregorio
Garcia-Sabater, Jose P.

Tipo de recurso:: Article of journal

Fecha de publicación:: 2019

Institución:: Corporación Universidad de la Costa

Repositorio:: REDICUC - Repositorio CUC

Idioma:: eng

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network_acronym_str	RCUC2
network_name_str	REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv	A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments
dc.title.translated.spa.fl_str_mv	Un algoritmo basado en listas tabú para el dimensionamiento de lotes de múltiples niveles capacitados con listas de materiales alternativas y entornos de coproducción
title	A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments
spellingShingle	A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments Materials requirements planning Lot sizing Flexible manufacturing systems Heuristic algorithms Operations research Tabu list GMOP Alternate bill of materials Coproduction Planificación de necesidades de materiales Tamaño de lote Sistemas de fabricación flexibles Heurístico algoritmos la investigación de operaciones Lista tabu Lista de materiales alternativos Coproducción
title_short	A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments
title_full	A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments
title_fullStr	A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments
title_full_unstemmed	A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments
title_sort	A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments
dc.creator.fl_str_mv	Romero-Conrado, Alfonso R. Coronado-Hernandez, Jairo R. Rius-Sorolla, Gregorio Garcia-Sabater, Jose P.
dc.contributor.author.spa.fl_str_mv	Romero-Conrado, Alfonso R. Coronado-Hernandez, Jairo R. Rius-Sorolla, Gregorio Garcia-Sabater, Jose P.
dc.subject.spa.fl_str_mv	Materials requirements planning Lot sizing Flexible manufacturing systems Heuristic algorithms Operations research Tabu list GMOP Alternate bill of materials Coproduction Planificación de necesidades de materiales Tamaño de lote Sistemas de fabricación flexibles Heurístico algoritmos la investigación de operaciones Lista tabu Lista de materiales alternativos Coproducción
topic	Materials requirements planning Lot sizing Flexible manufacturing systems Heuristic algorithms Operations research Tabu list GMOP Alternate bill of materials Coproduction Planificación de necesidades de materiales Tamaño de lote Sistemas de fabricación flexibles Heurístico algoritmos la investigación de operaciones Lista tabu Lista de materiales alternativos Coproducción
description	The definition of lot sizes represents one of the most important decisions in production planning. Lot-sizing turns into an increasingly complex set of decisions that requires efficient solution approaches, in response to the time-consuming exact methods (LP, MIP). This paper aims to propose a Tabu list-based algorithm (TLBA) as an alternative to the Generic Materials and Operations Planning (GMOP) model. The algorithm considers a multi-level, multi-item planning structure. It is initialized using a lot-for-lot (LxL) method and candidate solutions are evaluated through an iterative Material Requirements Planning (MRP) procedure. Three different sizes of test instances are defined and better results are obtained in the large and medium-size problems, with minimum average gaps close to 10.5%
publishDate	2019
dc.date.accessioned.none.fl_str_mv	2019-05-16T20:06:50Z
dc.date.available.none.fl_str_mv	2019-05-16T20:06:50Z
dc.date.issued.none.fl_str_mv	2019-04-03
dc.type.spa.fl_str_mv	Artículo de revista
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dc.type.content.spa.fl_str_mv	Text
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dc.identifier.issn.spa.fl_str_mv	20763417
dc.identifier.uri.spa.fl_str_mv	https://hdl.handle.net/11323/4173
dc.identifier.instname.spa.fl_str_mv	Corporación Universidad de la Costa
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identifier_str_mv	20763417 Corporación Universidad de la Costa REDICUC - Repositorio CUC
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dc.language.iso.none.fl_str_mv	eng
language	eng
dc.relation.ispartof.spa.fl_str_mv	DOI: 10.3390/app9071464
dc.relation.references.spa.fl_str_mv	Karimi, B.; Fatemi Ghomi, S.; Wilson, J. The capacitated lot sizing problem: A review of models and algorithms. Omega 2003, 31, 365–378. [CrossRef] Martí, R.; Reinelt, G. Heuristic Methods. In The Linear Ordering Problem; Springer: Berlin, Germany, 2011; pp. 17–40. [CrossRef] Barany, I.; Van Roy, T.J.; Wolsey, L.A. Strong Formulations for Multi-Item Capacitated Lot Sizing. Manag. Sci. 1984, 30, 1255–1261. [CrossRef] Eppen, G.D.; Martin, R.K. Solving Multi-Item Capacitated Lot-Sizing Problems Using Variable Redefinition. Oper. Res. 1987, 35, 832–848. [CrossRef] Maes, J.; McClain, J.O.; Van Wassenhove, L.N. Multilevel capacitated lotsizing complexity and LP-based heuristics. Eur. J. Oper. Res. 1991, 53, 131–148. [CrossRef] Buschkühl, L.; Sahling, F.; Helber, S.; Tempelmeier, H. Dynamic Capacitated Lot-Sizing Problems: A Classification and Review of Solution Approaches. OR Spectrum. 2010, 32, 231–261. [CrossRef] Drexl, A.; Kimms, A. Lot sizing and scheduling—Survey and extensions. Eur. J. Oper. Res. 1997, 99, 221–235. [CrossRef] Glock, C.H.; Grosse, E.H.; Ries, J.M. The lot sizing problem: A tertiary study. Int. J. Prod. Econ. 2014, 155, 39–51. [CrossRef] Kuik, R.; Salomon, M.; Van Wassenhove, L.N.; Maes, J. Linear Programming, Simulated Annealing and Tabu Search Heuristics for Lotsizing in Bottleneck Assembly Systems. IIE Trans. 1993, 25, 62–72. [CrossRef] AMPL Optimization Inc. Standard Price List—AMPL. Available online: https://ampl.com/products/ standard-price-list/ (accessed on 1 March 2019) Seeanner, F.; Almada-Lobo, B.; Meyr, H. Combining the principles of variable neighborhood decomposition search and the fix&optimize heuristic to solve multi-level lot-sizing and scheduling problems. Comput. Oper. Res. 2013, 40, 303–317. [CrossRef] Hung, Y.F.; Chien, K.L. A Multi-Class Multi-Level Capacitated Lot Sizing Model. J. Oper. Res. Soc. 2000, 51, 1309. [CrossRef] Kang, Y.; Albey, E.; Uzsoy, R. Rounding heuristics for multiple product dynamic lot-sizing in the presence of queueing behavior. Comput. Oper. Res. 2018, 100, 54–65. [CrossRef] Berretta, R.; França, P.M.; Armentano, V.A. Metaheuristic approaches for the multilevel resource-constrained lot-sizing problem with setup and lead times. Asia-Pac. J. Oper. Res. 2005, 22, 261–286. [CrossRef] Kimms, A. Competitive methods for multi-level lot sizing and scheduling: Tabu search and randomized regrets. Int. J. Prod. Res. 1996, 34, 2279–2298. [CrossRef] Oliva San Martín, C.D.; Ramírez Guzmán, G. Algoritmo de tipo búsqueda tabú para un problema de programación de horarios universitarios vespertinos. INGE CUC 2013, 9, 58–65. Maheut, J.; Garcia-Sabater, J.P. La matriz de operaciones y materiales y la matriz de operaciones y recursos, un nuevo enfoque para resolver el problema GMOP basado en el concepto del stroke. Dir. Y Organ. 2011, 45, 46–57. Maheut, J.; Garcia-Sabater, J.P.; Garcia-Sabater, J.J.; Valero Herrero, M. El Stroke y la Matriz de Operaciones y Materiales, nuevo enfoque para resolver el problema GMOP. In Proceedings of the 5th International Conference on Industrial Engineering and Industrial Management, Cartagena, Spain, 7–9 September 2011; pp. 884–893. Garcia-Sabater, J.P.; Maheut, J.; Marin-Garcia, J.A. A new formulation technique to model materials and operations planning: The generic materials and operations planning (GMOP) problem. Eur. J. Ind. Eng. 2013, 7, 119. [CrossRef] Maheut, J.; Garcia Sabater, J.P. Algorithm for complete enumeration based on a stroke graph to solve the supply network configuration and operations scheduling problem. J. Ind. Eng. Manag. 2013, 6, 779–795. [CrossRef] Roca Molina, A. Construcción de Algoritmo Aplicando Relajación Lagrangeana Para la Obtención de un límite Inferior Para el Problema de Lotificación en Sistemas Multinivel en Entornos de Coproducción y Listas de Materiales Alternativas. Ph.D. Thesis, Universidad Tecnológica de Bolívar, Cartagena, Colombia, 2016. Rius Sorolla, G.; Maheut, J.; Coronado-Hernandez, J.; Garcia-Sabater, J.P. Lagrangian relaxation of the GMOP model. In Proceedings of the 11th International Conference on Industrial Engineering and Industrial Management, Valencia, Spain, 5–6 July 2017. Rius-Sorolla, G.; Maheut, J.; Coronado-Hernandez, J.R.; Garcia-Sabater, J.P. Lagrangian relaxation of the generic materials and operations planning model. Cent. Eur. J. Oper. Res. 2018, 1–19. [CrossRef] Maheut, J.; Garcia-Sabater, J.P.; Mula, J. The Generic Materials and Operations Planning (GMOP) problem solved iteratively: A case study in multi-site context. In IFIP Advances in Information and Communication Technology; Springer: Berlin/Heidelberg, Germany, 2012; Volume 384, pp. 66–73. Maheut, J. Modelos y Algoritmos Basados en el Concepto Stroke Para la Planificación y Programación de Operaciones con Alternativas en Redes de Suministro. Ph.D. Thesis, Universitat Politècnica de València, Valencia, Spain, 2013, doi:10.4995/Thesis/10251/29290. Maheut, J.; Garcia-Sabater, J.P. A Parallelizable Heuristic for Solving the Generic Materials and Operations Planning in a Supply Chain Network: A Case Study from the Automotive Industry. In IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS; Springer: Berlin/Heidelberg, Germany, 2012; pp. 151–157. Coronado-Hernandez, J.R.; Simancas-Mateus, D.; Avila-Martinez, K.; Garcia-Sabater, J.P. Heuristic for Material and Operations Planning in Supply Chains with Alternative Product Structure. J. Eng. Appl. Sci. 2017, 12, 628–635. [CrossRef] Romero-Conrado, A.R. Algoritmo heurístico basado en listas tabú para la planificación de la producción en sistemas multinivel con listas de materiales alternativas y entornos de coproducción. Master’s Thesis, Universidad de la Costa, Barranquilla, Colombia, 2018; pp. 1–141. Glover, F. Tabu Search—Part I. ORSA J. Comput. 1989, 1, 190–206. [CrossRef] Glover, F.; Taillard, E. A user’s guide to tabu search. Ann. Oper. Res. 1993, 41, 1–28. [CrossRef] Batista, M.B.M.; Glover, F. Búsqueda Tabú. Intel. Artif. Rev. Iberoam. De Intel. Artif. 2003, 7, 29–48. Chelouah, R.; Siarry, P. Tabu Search applied to global optimization. Eur. J. Oper. Res. 2000, 123, 256–270. [CrossRef] Raza, S.A.; Akgunduz, A.; Chen, M.Y. A tabu search algorithm for solving economic lot scheduling problem. J. Heuristics 2006, 12, 413–426. [CrossRef] Cesaret, B.; Oguz, C.; Sibel Salman, F. A tabu search algorithm for order acceptance and scheduling. ˇ Comput. Oper. Res. 2012, 39, 1197–1205. [CrossRef] Li, X.; Baki, F.; Tian, P.; Chaouch, B.A. A robust block-chain based tabu search algorithm for the dynamic lot sizing problem with product returns and remanufacturing. Omega 2014, 42, 75–87. [CrossRef] Li, J.Q.; Pan, Q.K. Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm. Inf. Sci. 2014, 316, 487–502. [CrossRef] Hindi, K.S. Solving the single-item, capacitated dynamic lot-sizing problem with startup and reservation costs by tabu search. Comput. Ind. Eng. 1995, 28, 701–707. [CrossRef] Hindi, K.S. Solving the CLSP by a Tabu Search Heuristic. J. Oper. Res. Soc. 1996, 47, 151–161. [CrossRef] Gopalakrishnan, M.; Ding, K.; Bourjolly, J.M.; Mohan, S. A Tabu-Search Heuristic for the Capacitated Lot-Sizing Problem with Set-up Carryover. Manag. Sci. 2001, 47, 851–863. [CrossRef] Glover, F. Tabu Search—Part II. ORSA J. Comput. 1990, 2, 4–32. [CrossRef] Orlicky, J. Material Requirements Planning; McGraw-Hill: New York, NY, USA, 1975. Minitab 18. Overview for Create General Full Factorial Design, 2019. Available online: https://support.minitab.com/en-us/minitab/18/help-and-how-to/modeling-statistics/doe/howto/factorial/create-factorial-design/create-general-full-factorial/before-you-start/overview/ (accessed on 1 March 2019) Perttunen, J. On the Significance of the Initial Solution in Travelling Salesman Heuristics. J. Oper. Res. Soc. 1994, 45, 1131. [CrossRef] Escobar Z, A.H.; Gallego R, R.A.; Romero L, R.A. Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem. Ing. E Investig. 2011, 31, 127–143. Elaziz, M.A.; Mirjalili, S. A hyper-heuristic for improving the initial population of whale optimization algorithm. Knowl.-Based Syst. 2019, 172, 42–63. [CrossRef] Chen, C.F.; Wu, M.C.; Lin, K.H. Effect of solution representations on Tabu search in scheduling applications. Comput. Oper. Res. 2013, 40, 2817–2825. [CrossRef] Romero-Conrado, A.R. Tabu List Based Algorithm Datasets, 2019. Available online: https://github.com/ alfonsoromeroc/tlba-gmop (accessed on 1 March 2019)
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spelling	Romero-Conrado, Alfonso R.Coronado-Hernandez, Jairo R.Rius-Sorolla, GregorioGarcia-Sabater, Jose P.2019-05-16T20:06:50Z2019-05-16T20:06:50Z2019-04-0320763417https://hdl.handle.net/11323/4173Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The definition of lot sizes represents one of the most important decisions in production planning. Lot-sizing turns into an increasingly complex set of decisions that requires efficient solution approaches, in response to the time-consuming exact methods (LP, MIP). This paper aims to propose a Tabu list-based algorithm (TLBA) as an alternative to the Generic Materials and Operations Planning (GMOP) model. The algorithm considers a multi-level, multi-item planning structure. It is initialized using a lot-for-lot (LxL) method and candidate solutions are evaluated through an iterative Material Requirements Planning (MRP) procedure. Three different sizes of test instances are defined and better results are obtained in the large and medium-size problems, with minimum average gaps close to 10.5%La definición de tamaños de lotes representa una de las decisiones más importantes en la planificación de la producción. El tamaño del lote se convierte en un conjunto cada vez más complejo de decisiones que requieren enfoques de soluciones eficientes, en respuesta a los métodos exactos que consumen tiempo (LP, MIP). Este documento tiene como objetivo proponer un algoritmo basado en listas Tabu (TLBA) como alternativa al modelo de Planificación de Operaciones y Materiales Genéricos (GMOP). El algoritmo considera una estructura de planificación de múltiples niveles y múltiples elementos. Se inicializa utilizando un método de lote por lote (LxL) y las soluciones candidatas se evalúan a través de un procedimiento iterativo de Planificación de requisitos de materiales (MRP). Se definen tres tamaños diferentes de instancias de prueba y se obtienen mejores resultados en los problemas de tamaño grande y mediano, con brechas promedio mínimas cercanas al 10.5%Romero-Conrado, Alfonso R.-79bec917-9852-42cd-ade4-9b043b419596-0Coronado-Hernandez, Jairo R.-61946460-99b3-4b47-a0ed-8d099cd66b16-0Rius-Sorolla, Gregorio-2635f7b2-4f19-4a8c-b0e1-547cfab7e70a-0Garcia-Sabater, Jose P.-fa97034c-a7a8-4c6e-bb2c-cdb15ce77635-0engMDPI AGDOI: 10.3390/app9071464Karimi, B.; Fatemi Ghomi, S.; Wilson, J. The capacitated lot sizing problem: A review of models and algorithms. Omega 2003, 31, 365–378. [CrossRef] Martí, R.; Reinelt, G. Heuristic Methods. In The Linear Ordering Problem; Springer: Berlin, Germany, 2011; pp. 17–40. [CrossRef] Barany, I.; Van Roy, T.J.; Wolsey, L.A. Strong Formulations for Multi-Item Capacitated Lot Sizing. Manag. Sci. 1984, 30, 1255–1261. [CrossRef] Eppen, G.D.; Martin, R.K. Solving Multi-Item Capacitated Lot-Sizing Problems Using Variable Redefinition. Oper. Res. 1987, 35, 832–848. [CrossRef] Maes, J.; McClain, J.O.; Van Wassenhove, L.N. Multilevel capacitated lotsizing complexity and LP-based heuristics. Eur. J. Oper. Res. 1991, 53, 131–148. [CrossRef] Buschkühl, L.; Sahling, F.; Helber, S.; Tempelmeier, H. Dynamic Capacitated Lot-Sizing Problems: A Classification and Review of Solution Approaches. OR Spectrum. 2010, 32, 231–261. [CrossRef] Drexl, A.; Kimms, A. Lot sizing and scheduling—Survey and extensions. Eur. J. Oper. Res. 1997, 99, 221–235. [CrossRef] Glock, C.H.; Grosse, E.H.; Ries, J.M. The lot sizing problem: A tertiary study. Int. J. Prod. Econ. 2014, 155, 39–51. [CrossRef] Kuik, R.; Salomon, M.; Van Wassenhove, L.N.; Maes, J. Linear Programming, Simulated Annealing and Tabu Search Heuristics for Lotsizing in Bottleneck Assembly Systems. IIE Trans. 1993, 25, 62–72. [CrossRef] AMPL Optimization Inc. Standard Price List—AMPL. Available online: https://ampl.com/products/ standard-price-list/ (accessed on 1 March 2019) Seeanner, F.; Almada-Lobo, B.; Meyr, H. Combining the principles of variable neighborhood decomposition search and the fix&optimize heuristic to solve multi-level lot-sizing and scheduling problems. Comput. Oper. Res. 2013, 40, 303–317. [CrossRef] Hung, Y.F.; Chien, K.L. A Multi-Class Multi-Level Capacitated Lot Sizing Model. J. Oper. Res. Soc. 2000, 51, 1309. [CrossRef] Kang, Y.; Albey, E.; Uzsoy, R. Rounding heuristics for multiple product dynamic lot-sizing in the presence of queueing behavior. Comput. Oper. Res. 2018, 100, 54–65. [CrossRef] Berretta, R.; França, P.M.; Armentano, V.A. Metaheuristic approaches for the multilevel resource-constrained lot-sizing problem with setup and lead times. Asia-Pac. J. Oper. Res. 2005, 22, 261–286. [CrossRef] Kimms, A. Competitive methods for multi-level lot sizing and scheduling: Tabu search and randomized regrets. Int. J. Prod. Res. 1996, 34, 2279–2298. [CrossRef] Oliva San Martín, C.D.; Ramírez Guzmán, G. Algoritmo de tipo búsqueda tabú para un problema de programación de horarios universitarios vespertinos. INGE CUC 2013, 9, 58–65. Maheut, J.; Garcia-Sabater, J.P. La matriz de operaciones y materiales y la matriz de operaciones y recursos, un nuevo enfoque para resolver el problema GMOP basado en el concepto del stroke. Dir. Y Organ. 2011, 45, 46–57. Maheut, J.; Garcia-Sabater, J.P.; Garcia-Sabater, J.J.; Valero Herrero, M. El Stroke y la Matriz de Operaciones y Materiales, nuevo enfoque para resolver el problema GMOP. In Proceedings of the 5th International Conference on Industrial Engineering and Industrial Management, Cartagena, Spain, 7–9 September 2011; pp. 884–893. Garcia-Sabater, J.P.; Maheut, J.; Marin-Garcia, J.A. A new formulation technique to model materials and operations planning: The generic materials and operations planning (GMOP) problem. Eur. J. Ind. Eng. 2013, 7, 119. [CrossRef] Maheut, J.; Garcia Sabater, J.P. Algorithm for complete enumeration based on a stroke graph to solve the supply network configuration and operations scheduling problem. J. Ind. Eng. Manag. 2013, 6, 779–795. [CrossRef] Roca Molina, A. Construcción de Algoritmo Aplicando Relajación Lagrangeana Para la Obtención de un límite Inferior Para el Problema de Lotificación en Sistemas Multinivel en Entornos de Coproducción y Listas de Materiales Alternativas. Ph.D. Thesis, Universidad Tecnológica de Bolívar, Cartagena, Colombia, 2016. Rius Sorolla, G.; Maheut, J.; Coronado-Hernandez, J.; Garcia-Sabater, J.P. Lagrangian relaxation of the GMOP model. In Proceedings of the 11th International Conference on Industrial Engineering and Industrial Management, Valencia, Spain, 5–6 July 2017. Rius-Sorolla, G.; Maheut, J.; Coronado-Hernandez, J.R.; Garcia-Sabater, J.P. Lagrangian relaxation of the generic materials and operations planning model. Cent. Eur. J. Oper. Res. 2018, 1–19. [CrossRef] Maheut, J.; Garcia-Sabater, J.P.; Mula, J. The Generic Materials and Operations Planning (GMOP) problem solved iteratively: A case study in multi-site context. In IFIP Advances in Information and Communication Technology; Springer: Berlin/Heidelberg, Germany, 2012; Volume 384, pp. 66–73. Maheut, J. Modelos y Algoritmos Basados en el Concepto Stroke Para la Planificación y Programación de Operaciones con Alternativas en Redes de Suministro. Ph.D. Thesis, Universitat Politècnica de València, Valencia, Spain, 2013, doi:10.4995/Thesis/10251/29290. Maheut, J.; Garcia-Sabater, J.P. A Parallelizable Heuristic for Solving the Generic Materials and Operations Planning in a Supply Chain Network: A Case Study from the Automotive Industry. In IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS; Springer: Berlin/Heidelberg, Germany, 2012; pp. 151–157. Coronado-Hernandez, J.R.; Simancas-Mateus, D.; Avila-Martinez, K.; Garcia-Sabater, J.P. Heuristic for Material and Operations Planning in Supply Chains with Alternative Product Structure. J. Eng. Appl. Sci. 2017, 12, 628–635. [CrossRef] Romero-Conrado, A.R. Algoritmo heurístico basado en listas tabú para la planificación de la producción en sistemas multinivel con listas de materiales alternativas y entornos de coproducción. Master’s Thesis, Universidad de la Costa, Barranquilla, Colombia, 2018; pp. 1–141. Glover, F. Tabu Search—Part I. ORSA J. Comput. 1989, 1, 190–206. [CrossRef] Glover, F.; Taillard, E. A user’s guide to tabu search. Ann. Oper. Res. 1993, 41, 1–28. [CrossRef] Batista, M.B.M.; Glover, F. Búsqueda Tabú. Intel. Artif. Rev. Iberoam. De Intel. Artif. 2003, 7, 29–48. Chelouah, R.; Siarry, P. Tabu Search applied to global optimization. Eur. J. Oper. Res. 2000, 123, 256–270. [CrossRef] Raza, S.A.; Akgunduz, A.; Chen, M.Y. A tabu search algorithm for solving economic lot scheduling problem. J. Heuristics 2006, 12, 413–426. [CrossRef] Cesaret, B.; Oguz, C.; Sibel Salman, F. A tabu search algorithm for order acceptance and scheduling. ˇ Comput. Oper. Res. 2012, 39, 1197–1205. [CrossRef] Li, X.; Baki, F.; Tian, P.; Chaouch, B.A. A robust block-chain based tabu search algorithm for the dynamic lot sizing problem with product returns and remanufacturing. Omega 2014, 42, 75–87. [CrossRef] Li, J.Q.; Pan, Q.K. Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm. Inf. Sci. 2014, 316, 487–502. [CrossRef] Hindi, K.S. Solving the single-item, capacitated dynamic lot-sizing problem with startup and reservation costs by tabu search. Comput. Ind. Eng. 1995, 28, 701–707. [CrossRef] Hindi, K.S. Solving the CLSP by a Tabu Search Heuristic. J. Oper. Res. Soc. 1996, 47, 151–161. [CrossRef] Gopalakrishnan, M.; Ding, K.; Bourjolly, J.M.; Mohan, S. A Tabu-Search Heuristic for the Capacitated Lot-Sizing Problem with Set-up Carryover. Manag. 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Knowl.-Based Syst. 2019, 172, 42–63. [CrossRef] Chen, C.F.; Wu, M.C.; Lin, K.H. Effect of solution representations on Tabu search in scheduling applications. Comput. Oper. Res. 2013, 40, 2817–2825. [CrossRef] Romero-Conrado, A.R. Tabu List Based Algorithm Datasets, 2019. Available online: https://github.com/ alfonsoromeroc/tlba-gmop (accessed on 1 March 2019)http://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Materials requirements planningLot sizingFlexible manufacturing systemsHeuristic algorithmsOperations researchTabu listGMOPAlternate bill of materialsCoproductionPlanificación de necesidades de materialesTamaño de loteSistemas de fabricación flexiblesHeurístico algoritmosla investigación de operacionesLista tabuLista de materiales alternativosCoproducciónA tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environmentsUn algoritmo basado en listas tabú para el dimensionamiento de lotes de múltiples niveles capacitados con listas de materiales alternativas y entornos de coproducciónArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionPublicationORIGINALA Tabu List-Based Algorithm for Capacitated.pdfA Tabu List-Based Algorithm for Capacitated.pdfapplication/pdf471820https://repositorio.cuc.edu.co/bitstreams/bb5e0ee4-e3f2-4d5a-a7d6-3492c4880250/download76da99d8a26bed68a465bbcdf1bf89b8MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81031https://repositorio.cuc.edu.co/bitstreams/3f979826-4441-477d-919b-4ee020d9f355/download934f4ca17e109e0a05eaeaba504d7ce4MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/a86a185a-4327-48f4-a047-f76209ffbb83/download8a4605be74aa9ea9d79846c1fba20a33MD53THUMBNAILA Tabu List-Based Algorithm for Capacitated.pdf.jpgA Tabu List-Based Algorithm for Capacitated.pdf.jpgimage/jpeg67911https://repositorio.cuc.edu.co/bitstreams/3d328ad8-ab9a-4bdc-94ba-c5ef118a7f27/download81776e56752da59f7bfd299b60241c3fMD55TEXTA Tabu List-Based Algorithm for Capacitated.pdf.txtA Tabu List-Based Algorithm for Capacitated.pdf.txttext/plain44151https://repositorio.cuc.edu.co/bitstreams/ea3b40f5-68fe-4934-b025-217dea79bd7c/download5118805b5149ce4d8d1f936edc739195MD5611323/4173oai:repositorio.cuc.edu.co:11323/41732024-09-17 12:48:26.277http://creativecommons.org/licenses/by-nc-sa/4.0/open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.coTk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo=

A tabu list-based algorithm for capacitated multilevel lot-sizing with alternate bills of materials and co-production environments

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