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The Uniform Parallel Machine Scheduling Problem: A Case Study

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Proceedings of the International Symposium for Production Research 2019 (ISPR 2019, ISPR 2019)

Abstract

In this study, the uniform parallel machine scheduling problem with non-common due dates and sequence-dependent setup times is addressed for a real-life problem in the dye house of a hood manufacturer company. The aim of this study is to create an efficient scheduling tool for the company, which minimizes lateness (earliness and tardiness) in the system and reduces the buffer stock caused by the lateness. A mathematical model is developed for the problem and optimal results are obtained for the small-sized instances. As the studied problem is NP-hard, three heuristic algorithms are also proposed to solve larger instances. The performance of the proposed algorithms is evaluated with a detailed computational experiment. Furthermore, a user-friendly decision support system (DSS) is developed using Excel VBA interface and proposed solution approaches are embedded in the DSS. The developed DSS enables users to make an efficient scheduling in very short computational time and provides the results with detailed schedule reports and Gantt charts. As this problem can be faced in various industrial areas, the proposed solution approaches can also be applied to different sectors and factories.

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Acknowledgment

This work cannot be completed without the assistance of Kaan Özsümbül and Batuhan Uğuz. We are thankful for their contribution. Furthermore, we are grateful to the company for their co-operation.

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Correspondence to Hande Öztop .

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Duran, E. et al. (2020). The Uniform Parallel Machine Scheduling Problem: A Case Study. In: Durakbasa, N., Gençyılmaz, M. (eds) Proceedings of the International Symposium for Production Research 2019. ISPR ISPR 2019 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-31343-2_69

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  • DOI: https://doi.org/10.1007/978-3-030-31343-2_69

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31342-5

  • Online ISBN: 978-3-030-31343-2

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