| dc.description.abstract | Improved storage location assignment of newly delivered products is one effective
method for improving the order picking operation performance, especially the
warehouse is mostly serviced by human pickers. This study aims to identify a potential
solution by developing a distributed, adaptive strategy Cube-per-Oder index based
method (COI) for the storage location assignment problem and follows the demand
correlation pattern paradigm for its implementation. The proposed model is specially
formulated to distribute SKUs that are prevalently ordered together in positions close to
one another, add in the criteria that frequently ordered ones near the I/O (input/output)
point. Consequently, the experiment results reveal that the items re-assignment is totally
helpful to reduce the travel distance of order picker in distribution center when
comparing to the existing random storage practice. The efficiency of such a strategy in
real industrial systems is explored via a computational study using the empirical data
from a real-case warehouse, particularly YCH Protrade. | en_US |
