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A class-based storage warehouse design using a particle swarm optimisation algorithm

Author

Listed:
  • Natanaree Sooksaksun
  • Voratas Kachitvichyanukul
  • Dah-Chuan Gong

Abstract

Classical warehouse design is commonly done in two steps by first determining the aisle layout and dimension followed by the assignment of items to storage. The design process is performed iteratively until a design with appropriate performance criterion is found. This paper proposes an approach for warehouse design in one step by determining the aisle layout and dimension while simultaneously assigning shelf spaces for storing the items based on item classes. A mathematical model is formulated to determine the number of aisles, the length of aisle and the length of each pick aisle to allocate to each product class that will minimise the average travel distance for a warehouse that operates under a class-based storage policy. A particle swarm optimisation algorithm was developed to determine the optimal warehouse design. The proposed method not only accomplishes the task in one step but also can identify multiple alternative designs. A case study is used to illustrate the proposed algorithm.

Suggested Citation

  • Natanaree Sooksaksun & Voratas Kachitvichyanukul & Dah-Chuan Gong, 2012. "A class-based storage warehouse design using a particle swarm optimisation algorithm," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 13(2), pages 219-237.
    • Handle: RePEc:ids:ijores:v:13:y:2012:i:2:p:219-237
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    Cited by:

    1. 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).
    2. Mital, Pratik & Goetschalckx, Marc & Huang, Edward, 2015. "Robust material handling system design with standard deviation, variance and downside risk as risk measures," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 815-824.

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