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Simultaneous determination of warehouse layout and control policies

Author

Listed:
  • Kees Jan Roodbergen
  • Iris F.A. Vis
  • G. Don Taylor

Abstract

In a supply chain’s order fulfilment process, it is often the warehouse that plays a central role in making the right product available to the right customer at the right time. This paper aims to improve warehouse performance by deriving an effective design method for the simultaneous determination of warehouse layout and the warehouse’s control policies. The authors consider layout variables for the warehouse such as the number of primary aisles utilised, the number of cross-aisles and the aisle length under several different design philosophies. Concurrently, control policies such as storage policies and routing are considered. Simulation is utilised to determine the performance of the various resulting scenarios. A screening and selection procedure is employed to reduce the required number of replications while achieving a predetermined precision in identifying the best configuration. The approach is applied for an industrial partner in this research and the results of experimentation are compared to a baseline scenario which describes a proposed new facility in the Netherlands. The results reveal a large potential for performance improvement.

Suggested Citation

  • Kees Jan Roodbergen & Iris F.A. Vis & G. Don Taylor, 2015. "Simultaneous determination of warehouse layout and control policies," International Journal of Production Research, Taylor & Francis Journals, vol. 53(11), pages 3306-3326, June.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:11:p:3306-3326
    DOI: 10.1080/00207543.2014.978029
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    Citations

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    Cited by:

    1. Dong, Wenquan & Jin, Mingzhou, 2024. "Automated storage and retrieval system design with variant lane depths," European Journal of Operational Research, Elsevier, vol. 314(2), pages 630-646.
    2. Li Zhou & Huwei Liu & Junhui Zhao & Fan Wang & Jianglong Yang, 2022. "Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse," Mathematics, MDPI, vol. 10(17), pages 1-28, September.
    3. Kateryna Czerniachowska & Radosław Wichniarek & Krzysztof Żywicki, 2023. "A Model for an Order-Picking Problem with a One-Directional Conveyor and Buffer," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    4. Silva, Allyson & Roodbergen, Kees Jan & Coelho, Leandro C. & Darvish, Maryam, 2022. "Estimating optimal ABC zone sizes in manual warehouses," International Journal of Production Economics, Elsevier, vol. 252(C).
    5. van Gils, Teun & Caris, An & Ramaekers, Katrien & Braekers, Kris & de Koster, René B.M., 2019. "Designing efficient order picking systems: The effect of real-life features on the relationship among planning problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 47-73.
    6. Heiko Diefenbach & Simon Emde & Christoph H. Glock & Eric H. Grosse, 2022. "New solution procedures for the order picker routing problem in U-shaped pick areas with a movable depot," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 535-573, June.
    7. Glock, Christoph H. & Grosse, Eric H. & Abedinnia, Hamid & Emde, Simon, 2019. "An integrated model to improve ergonomic and economic performance in order picking by rotating pallets," European Journal of Operational Research, Elsevier, vol. 273(2), pages 516-534.
    8. Deniz Preil & Michael Krapp, 2022. "Artificial intelligence-based inventory management: a Monte Carlo tree search approach," Annals of Operations Research, Springer, vol. 308(1), pages 415-439, January.
    9. Neves-Moreira, Fábio & Amorim, Pedro, 2024. "Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail," International Journal of Production Economics, Elsevier, vol. 267(C).
    10. Masae, Makusee & Glock, Christoph H. & Vichitkunakorn, Panupong, 2021. "A method for efficiently routing order pickers in the leaf warehouse," International Journal of Production Economics, Elsevier, vol. 234(C).
    11. AERTS, Babiche & CORNELISSENS, Trijntje & SÖRENSEN, Kenneth, 2022. "The internal warehouse replenishment problem: the importance of storage and replenishment policies," Working Papers 2022007, University of Antwerp, Faculty of Business and Economics.
    12. Xuan Zhang & Tiantian Mo & Yougong Zhang, 2023. "Optimization of Storage Location Assignment for Non-Traditional Layout Warehouses Based on the Firework Algorithm," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    13. van Gils, Teun & Ramaekers, Katrien & Caris, An & de Koster, René B.M., 2018. "Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review," European Journal of Operational Research, Elsevier, vol. 267(1), pages 1-15.
    14. Dragan Djurdjević & Nenad Bjelić & Dražen Popović & Milan Andrejić, 2022. "A Combined Dynamic Programming and Simulation Approach to the Sizing of the Low-Level Order-Picking Area," Mathematics, MDPI, vol. 10(20), pages 1-23, October.
    15. Derhami, Shahab & Smith, Jeffrey S. & Gue, Kevin R., 2020. "A simulation-based optimization approach to design optimal layouts for block stacking warehouses," International Journal of Production Economics, Elsevier, vol. 223(C).
    16. Silva, Allyson & Coelho, Leandro C. & Darvish, Maryam & Renaud, Jacques, 2020. "Integrating storage location and order picking problems in warehouse planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).

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