Abstract
In this paper, a real-life parallel machine scheduling problem with sequence-dependent setup times of an industrial-type electrical equipment manufacturing company is addressed. The objective of this study is to find a solution method to achieve an effective and systematic schedule that minimizes the total weighted tardiness in the system by considering some properties related to the jobs and machines. These properties are the priority rank of jobs, sequence-dependent setup times between jobs, machine eligibility, and machine availability. Initially, a mathematical model is proposed for the problem. The solving performance of the proposed model by LINGO is tested with randomly generated toy problems. Since the problem has NP-hard characteristics, heuristic algorithms based on the EDD rule and GTW algorithm are developed to obtain optimal or near-optimal schedules in an acceptable period of time. The success of the algorithms is tested through generated toy problems. It is observed that the combination of Modified EDD and HENOBA algorithms gives optimal or near-optimal solutions. Lastly, an efficient and user-friendly decision support system (DSS) is created.
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References
Hassin, R., Shani, M.: Machine scheduling with earliness, tardiness and non-execution penalties. Comput. Operations Res. 32(3), 683–705 (2005). doi:https://doi.org/10.1016/j.cor.2003.08.012
Ho, J. C., Chang, Y.: Heuristics for minimizing mean tardiness form parallel machines. Naval Res. Logist. 38-381 (1991)
Kim, J., Song, S., Jeong, B.: Minimising total tardiness for the identical parallel machine scheduling problem with splitting jobs and sequence-dependent setup times. Int. J. Production Res. 58(6), 1628–1643 (2019). https://doi.org/10.1080/00207543.2019.1672900
Lee, Y. H., Pinedo, M.: Scheduling jobs on parallel machines with sequence-dependent setup times. European J. Operat. Res. 100(3), 464–474 (1997)
Pinedo, M.L.: Scheduling: Theory, Algorithms, and Systems, 3rd edn. Prentice Hall, New York, NY (2008). https://doi.org/10.1007/978-0-387-78935-4
Radhakrishnan, S., Ventura, J.A.: Simulated annealing for parallel machine scheduling with earliness-tardiness penalties and sequence-dependent set-up times. Int. J. Product. Res. 38(10), 2233–2252 (2000). https://doi.org/10.1080/00207540050028070
Zhu, Z., Heady, R.B.: . Minimizing the sum of earliness/tardiness in multi-machine scheduling: a mixed integer programming approach. Comput. Indust. Eng. 38(2), 297–305 (2000). https://doi.org/10.1016/S0360-8352(00)00048-6
Acknowledgment
This study is supported in the program “2209-B - Industry Oriented Research Project Support Programme for Undergraduate Students” by The Scientific and Technological Research Council of Turkey (TUBITAK).
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Aldemir, A. et al. (2023). Job Scheduling Problem in the Production of Electrical Equipment. In: Durakbasa, N.M., Gençyılmaz, M.G. (eds) Towards Industry 5.0. ISPR 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-24457-5_65
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