TY - JOUR
T1 - Robust storage assignment in warehouses with correlated demand
AU - Kofler, Monika
AU - Beham, Andreas
AU - Wagner, Stefan
AU - Affenzeller, Michael
N1 - Funding Information:
This paper is an updated and extended version of [] 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).
Publisher Copyright:
© Springer International Publishing Switzerland 2015
PY - 2015
Y1 - 2015
N2 - 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 productsmight 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-worldwarehouse robust slotting outperformed greedy re-locations by up to 9.6%.
AB - 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 productsmight 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-worldwarehouse robust slotting outperformed greedy re-locations by up to 9.6%.
UR - http://www.scopus.com/inward/record.url?scp=84924975567&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-15720-7_29
DO - 10.1007/978-3-319-15720-7_29
M3 - Article
AN - SCOPUS:84924975567
SN - 1860-949X
VL - 595
SP - 415
EP - 428
JO - Studies in Computational Intelligence
JF - Studies in Computational Intelligence
ER -