Abstract
There has been a wealth of research on warehouse optimization since the 1960s, and in particular on increasing order picking efficiency, which is one of the most labor intensive processes in many logistics centers. In the last ten years, affinity based slotting strategies, which place materials that are frequently ordered/picked together close to each other, have started to emerge. However, the effects of changing customer demand patterns on warehousing efficiency have not been investigated in detail. The aim of this chapter is to extend the classic storage location assignment problem (SLAP) to a multi-period formulation (M-SLAP) and to test and compare how various allocation rules, and in particular an affinity based policy, perform in such dynamic scenarios. A first benchmark instance for the M-SLAP is presented.
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Keywords
- Storage Location
- Benchmark Instance
- Facility Layout Problem
- Order Picking
- Dynamic Facility Layout Problem
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Kofler, M., Beham, A., Wagner, S., Affenzeller, M. (2014). Affinity Based Slotting in Warehouses with Dynamic Order Patterns. In: Klempous, R., Nikodem, J., Jacak, W., Chaczko, Z. (eds) Advanced Methods and Applications in Computational Intelligence. Topics in Intelligent Engineering and Informatics, vol 6. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01436-4_7
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DOI: https://doi.org/10.1007/978-3-319-01436-4_7
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