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Comparison between rule- and optimization-based workload control concepts: a simulation optimization approach

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  • Stefan Haeussler
  • Pia Netzer

Abstract

An important goal of Production Planning and Control systems is to achieve short and predictable flow times, especially where high flexibility in meeting customer demand is required, while maintaining high output and due-date performance. One approach to this problem is the workload control (WLC) concept. Within WLC research two directions have been developed, largely separately, over time: Rule based and optimisation-based models. If a company intends to introduce an order release concept based on WLC it first has to decide which of these two approaches should be applied. Therefore, this paper compares two of the most widely used and considered best performing periodic order release models out of both streams: the LUMS (rule based) and the clearing function model (optimisation based). The parameters of both approaches are set using simulation optimisation. The performance is compared using a simulation study of a hypothetical job shop in a rolling horizon setting. The results show that the optimisation model outperforms the rule-based mechanism in all instances with stochastic demand (exponential inter-arrival times), but is outperformed in aggregate cost of backorders and inventory holding and balancing measures by the LUMS approach for scenarios with high utilisation and seasonal demand.

Suggested Citation

  • Stefan Haeussler & Pia Netzer, 2020. "Comparison between rule- and optimization-based workload control concepts: a simulation optimization approach," International Journal of Production Research, Taylor & Francis Journals, vol. 58(12), pages 3724-3743, June.
  • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:12:p:3724-3743
    DOI: 10.1080/00207543.2019.1634297
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    Cited by:

    1. Kasper, T.A. Arno & Land, Martin J. & Teunter, Ruud H., 2023. "Non-hierarchical work-in-progress control in manufacturing," International Journal of Production Economics, Elsevier, vol. 257(C).
    2. Ghadimi, Foad & Aouam, Tarik & Haeussler, Stefan & Uzsoy, Reha, 2022. "Integrated and hierarchical systems for coordinating order acceptance and release planning," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1277-1289.
    3. Kasper, T.A. Arno & Land, Martin J. & Teunter, Ruud H., 2023. "Towards System State Dispatching in High‐Variety Manufacturing," Omega, Elsevier, vol. 114(C).
    4. Stefan Haeussler & Philipp Neuner & Matthias Thürer, 2023. "Balancing earliness and tardiness within workload control order release: an assessment by simulation," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 487-508, June.
    5. Matthias Thürer & Mark Stevenson, 2021. "Material handling and order release control in high-variety make-to-order shops: an assessment by simulation," Operations Management Research, Springer, vol. 14(3), pages 494-506, December.

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