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Class-Based Storage Assignment in a Unit-Load Warehouse Employing AS/RS with Inventory Space Allocation Considering Product Specific Setup to Holding Cost Ratio

Author

Listed:
  • Subir S. Rao

    (Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India)

  • Gajendra K. Adil

    (Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India)

Abstract

Many authors have used continuous optimization models for class-based storage allocation for unit load warehouses employing AS/RS system assuming the same setup to holding cost ratio for all products in their EOQ inventory policy. Accordingly, an ABC curve based on demand ordering of products is used to determine pallet turnovers in their travel distance models which is not applicable in many practical situations and can be inaccurate. This paper develops a new model to determine two/three class optimal partitions while relaxing assumption of constant setup to holding cost ratio in the EOQ formula and as a consequence uses an ABC curve based on decreasing ranking of product turnovers rather than that based on demand. Computational experience shows that this new continuous model approximates pick travel distances which are very close to as compared to that of a semi-discrete model (SDM) proposed in this paper. Further computational experiments are also provided comparing traditional models with our formulations.

Suggested Citation

  • Subir S. Rao & Gajendra K. Adil, 2014. "Class-Based Storage Assignment in a Unit-Load Warehouse Employing AS/RS with Inventory Space Allocation Considering Product Specific Setup to Holding Cost Ratio," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 31(05), pages 1-22.
    • Handle: RePEc:wsi:apjorx:v:31:y:2014:i:05:n:s0217595914500341
    DOI: 10.1142/S0217595914500341
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    Cited by:

    1. Claeys, Dieter & Adan, Ivo & Boxma, Onno, 2016. "Stochastic bounds for order flow times in parts-to-picker warehouses with remotely located order-picking workstations," European Journal of Operational Research, Elsevier, vol. 254(3), pages 895-906.

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