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Cross-Docking Layout Optimization in FlexSim Software Based on Cold Chain 4PL Company

Author

Listed:
  • Augustyn Lorenc

    (Faculty of Mechanical Engineering, Cracow University of Technology, 31-864 Cracow, Poland)

Abstract

The paper highlights the potential of cross-docking to reduce storage time and costs. The study addresses evolving market demands that push logistics providers to adopt new technologies for operational efficiency, emphasizing the often-overlooked importance of optimizing cross-docking layouts. The research, conducted in two phases, first analyzed the current warehouse layout (Variant I) to identify inefficiencies and then designed a new layout (Variant II) that was simulated using FlexSim 2022 software. The results showed significant improvements with the new layout, including a 35% increase in deliveries and a 3.23% reduction in forklift travel distances, leading to lower operational costs. Even minor adjustments in the warehouse design proved to enhance logistics efficiency, particularly during peak demand periods like holidays. The study demonstrates how FlexSim software can be applied in cold chain logistics to optimize warehouse operations, underscoring the benefits of cross-docking for cost-effective logistics management.

Suggested Citation

  • Augustyn Lorenc, 2024. "Cross-Docking Layout Optimization in FlexSim Software Based on Cold Chain 4PL Company," Sustainability, MDPI, vol. 16(22), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9620-:d:1514182
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    References listed on IDEAS

    as
    1. Konstantinos Petridis & Prasanta Kumar Dey & Ali Emrouznejad, 2017. "A branch and efficiency algorithm for the optimal design of supply chain networks," Annals of Operations Research, Springer, vol. 253(1), pages 545-571, June.
    2. Roodbergen, Kees Jan & de Koster, Rene, 2001. "Routing order pickers in a warehouse with a middle aisle," European Journal of Operational Research, Elsevier, vol. 133(1), pages 32-43, August.
    3. Haoxuan Yu & Izni Zahidi, 2023. "Tailings Pond Classification Based on Satellite Images and Machine Learning: An Exploration of Microsoft ML.Net," Mathematics, MDPI, vol. 11(3), pages 1-14, January.
    Full references (including those not matched with items on IDEAS)

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