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Constraint Programming for Flexible Flow Shop Scheduling Problem with Repeated Jobs and Repeated Operations

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EN
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EN
The manufacturing process relies heavily on production scheduling to guarantee effective production schedules, reduce costs and product shortages, and get away from delays, interruptions, and waste products. Scheduling issues have been effectively solved via constraint programming. In this paper, we consider a constraint programming formulation of the flexible flow shop scheduling problem with repeated jobs and operations repetitions. We also implemented seven fast heuristics and compared the results with the constraint programming solution. The results from using the CPLEX solver as a solution tool were satisfactory. Computational experiments demonstrate that using constraint programming can be significantly more advantageous than using heuristics.
Twórcy
Bibliografia
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  • 2. Teppan, E. (2022). Types of Flexible Job Shop Scheduling: A Constraint Programming Experiment. Proceedings of the 14th International Conference on Agents and Artificial Intelligence, Vol. 3: ICAART, 516–523. https://doi. org/10.5220/0010849900003116
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  • 8. Da Col, G. and Teppan, E.C. (2022). Industrial-size job shop scheduling with constraint programming. Operations Research Perspectives, 9, 100249. DOI: https://doi.org/10.1016/j.orp.2022.100249
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  • 14. Abderrahim, M., Bekrar, A., Trentesaux, D., Aissani, N., and Bouamrane, K. (2022). Bi-local search based variable neighborhood search for job-shop scheduling problem with transport constraints. Optimization Letters, 16(1), 255–280. DOI: https://doi. org/10.1007/s11590-020-01674-0
  • 15. Respen, J., Zufferey, N., and Amaldi, E. (2016). Metaheuristics for a job scheduling problem with smoothing costs relevant for the car industry. Networks, 67(3), 246–261. DOI: https://doi. org/10.1002/net.21656
  • 16. Homayouni, S.M. and Fontes, D.B.M.M. (2021). Production and transport scheduling in flexible job shop manufacturing systems. Journal of Global Optimization, 79(2), 463–502. DOI: https://doi. org/10.1007/s10898-021-00992-6
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  • 22. Ruiz, R. and Vázquez-Rodríguez, J. A. (2010). The hybrid flow shop scheduling problem. European Journal of Operational Research, 205(1), 1–18. DOI: https://doi.org/10.1016/j.ejor.2009.09.024
  • 23. Hasani, A., Hosseini, S.M.H., and Sana, S.S. (2022). Scheduling in a flexible flow shop with unrelated parallel machines and machine-dependent proces stages: Trade-off between Makespan and production costs. Sustainability Analytics and Modeling, 2, 100010. DOI: ttps://doi.org/10.1016/j. samod.2022.100010
  • 24. Ribas, I., Leisten, R., and Framinan, J.M. (2010). Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective. Computers and Operations Research, 37(8), 1439–1454). DOI: https://doi.org/10.1016/j.cor.2009.11.001
  • 25. Eskandari, H. and Hosseinzadeh, A. (2014). A variable neighbourhood search for hybrid flow-shop scheduling problem with rework and set-up times. Journal of the Operational Research Society, 65(8), 1221–1231. DOI: https://doi.org/10.1057/jors.2013.70
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  • 27. De Abreu, L.R., Araújo, K.A.G., de Athayde Prata, B., Nagano, M.S., and Moccellin, J.V. (2022). A new variable neighbourhood search with a constraint programming search strategy for the open shop scheduling problem with operation repetitions. Engineering Optimization, 54(9), 1563–1582. DOI: https://doi.org/10.1080/0305215X.2021.1957101
  • 28. Roundy, R., Chen, D., Chen, P., Çakanyildirim, M., Freimer, M.B., and Melkonian, V. (2005). Capacity- driven acceptance of customer orders for a multistage batch manufacturing system: Models and algorithms. IIE Transactions (Institute of Industrial Engineers), 37(12), 1093–1105. DOI: https://doi. org/10.1080/07408170500288042
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Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cfc0fc11-fc15-4719-bc0b-1512870e3c1a
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