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Optimization of buffer allocations in flow lines with limited supply

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  • Sophie Weiss
  • Andrea Matta
  • Raik Stolletz

Abstract

The supply of flow lines is often assumed to be unlimited or to follow certain distributions. However, this assumption may not always be realistic, as flow lines are usually an integral part of a supply chain where raw material is replenished based on some rule. We therefore include the limited supply into the optimization of buffer capacities in terms of an order policy.To integrate this type of supply into an optimization model, we exploit the flexibility of a sample-based optimization approach. We develop an efficient rule-based local search algorithm that employs new individual lower bounds in order to determine the optimal buffer capacities of a flow line. In addition to the efficiency of the proposed algorithm, the numerical study demonstrates that the order policy has a significant impact on the optimal buffer allocation.

Suggested Citation

  • Sophie Weiss & Andrea Matta & Raik Stolletz, 2018. "Optimization of buffer allocations in flow lines with limited supply," IISE Transactions, Taylor & Francis Journals, vol. 50(3), pages 191-202, March.
    • Handle: RePEc:taf:uiiexx:v:50:y:2018:i:3:p:191-202
    DOI: 10.1080/24725854.2017.1328751
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    Cited by:

    1. Mehmet Ulaş Koyuncuoğlu & Leyla Demir, 2021. "A comparison of combat genetic and big bang–big crunch algorithms for solving the buffer allocation problem," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1529-1546, August.
    2. Ziwei Lin & Nicla Frigerio & Andrea Matta & Shichang Du, 2021. "Multi-fidelity surrogate-based optimization for decomposed buffer allocation problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 223-253, March.
    3. Sachs, F.E. & Helber, S. & Kiesmüller, G.P., 2022. "Evaluation of Unreliable Flow Lines with Limited Buffer Capacities and Spare Part Provisioning," European Journal of Operational Research, Elsevier, vol. 302(2), pages 544-559.

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