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Computational Intelligence and Efficiency in Engineering Systems pp 415–428Cite as

Robust Storage Assignment in Warehouses with Correlated Demand

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 595))

Abstract

In many warehouses manual order picking is one of the most time and labour intensive processes. Products that are often ordered together are said to be correlated or affine and order picking performance may be improved by placing correlated products close to each other. In industries with strong seasonality patterns and fluctuating demand regular re-locations of products might be necessary to ensure that the quality of the storage assignment does not deteriorate over time. In this chapter we study how to generate more robust assignments that are suitable for volatile warehouse scenarios with correlated demand. In a case study based on 13 monthly snapshots from a real-world warehouse robust slotting outperformed greedy re-locations by up to 9.6 %.

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Notes

  1. 1.

    A detailed description of the multi-period SLAP and experimental results can be found in [11].

  2. 2.

    Experiments in [13] showed that moving a limited amount of items can significantly improve picker performance. By re-locating only 60 pallets in a warehouse with more than 1,400 pallets a reduction of picker travel distances of 23 % could be achieved. Conversely, almost the entire stock would have to be moved to realise a 60 % reduction.

  3. 3.

    The multi-period SLAP benchmark instance is available for download via

    http://dev.heuristiclab.com/trac/hl/core/wiki/AdditionalMaterial.

  4. 4.

    HeuristicLab and ELKI are free software and available via

    http://dev.heuristiclab.com/ and http://elki.dbs.ifi.lmu.de/.

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Acknowledgments

This paper is an updated and extended version of [12] and was first presented at the APCASE 2014 conference. The work described in this chapter was done within the Josef Ressel-Centre HEUREKA! for Heuristic Optimization sponsored by the Austrian Research Promotion Agency (FFG).

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Authors and Affiliations

  1. Heuristic and Evolutionary Algorithms Laboratory (HEAL), University of Applied Sciences Upper Austria, Softwarepark 11, 4232, Hagenberg, Austria

    Monika Kofler, Andreas Beham, Stefan Wagner & Michael Affenzeller

Authors
  1. Monika Kofler
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  2. Andreas Beham
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  3. Stefan Wagner
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  4. Michael Affenzeller
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Corresponding author

Correspondence to Monika Kofler .

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Editors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Grzegorz Borowik

  2. University of Technology, Sydney, New South Wales, Australia

    Zenon Chaczko

  3. University of Applied Sciences Upper Austria, Hagenberg, Austria

    Witold Jacak

  4. Warsaw University of Technology, Warsaw, Poland

    Tadeusz Łuba

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Kofler, M., Beham, A., Wagner, S., Affenzeller, M. (2015). Robust Storage Assignment in Warehouses with Correlated Demand. In: Borowik, G., Chaczko, Z., Jacak, W., Łuba, T. (eds) Computational Intelligence and Efficiency in Engineering Systems. Studies in Computational Intelligence, vol 595. Springer, Cham. https://doi.org/10.1007/978-3-319-15720-7_29

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  • DOI: https://doi.org/10.1007/978-3-319-15720-7_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15719-1

  • Online ISBN: 978-3-319-15720-7

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