Abstract
Considering time-varying demand of online retail industry, the traditional static storage location assignment is converted into a multistage storage location assignment process based on the idea of gradual and small-step-forward optimization, which can respond to rapid changes in demand by adjusting the storage location of SKUs in the warehouse in real time and dynamically. First, the study formulates the framework dynamic storage location assignment. Then, the adjustment gain model of dynamic storage location assignment is built, and a genetic algorithm is designed to find the final adjustment solution. Finally, the computer program is developed to simulate the whole process. Simulation and data analysis results show that dynamic storage location assignment can effectively improve picking efficiency when the average order size is small and large demand correlation strength. Dynamic storage location assignment simplifies the warehouse operation process by combining the picking operation and storage location assignment into one without changing the picker’s current walking route, which can offer some theoretical guidance for online retail enterprises implementing dynamic storage location assignment.
Highlights
Online retail enterprises should deliver commodities at a lower cost and a faster speed, and order picking is an important part of customer order delivery, which becomes the key to success for online retail enterprises
Considering that DSLA needs to move the SKUs with high popularity from areas far away from P/D to the area close to P/D, we propose a backward-traversing routing method, in which the picker first walks along the north cross to the last aisle containing SKUs to be picked and picks SKUs from east to west under the S-shaped routing method
DSLA adjusts the SKUs with high popularity to the storage zone near the P/D, and it adjusts the SKUs with demand correlation to the same or adjacent storage locations
Summary
Online retail enterprises should deliver commodities at a lower cost and a faster speed, and order picking is an important part of customer order delivery, which becomes the key to success for online retail enterprises. DSLA transfers the traditional storage location assignment into multistage dynamic storage location assignment based on the step-by-step way, which optimizes SKU’s storage location gradually instead of the traditional one-time optimization It moves a small part of SKUs to meet the demand from one area of the warehouse to another periodically and gradually improve and optimize the storage structure of the warehouse. Due to the high idle cost of the aisle-bound cranes of the AS/RS system, Christofides and Colloff [12] studied the DSLA problem of the AS/RS system very early, and many other studies carried out related research, but there were few DSLA studies of picker-to-parts picking systems Both picker-to-parts picking and AS/RS systems optimize the storage structure of a warehouse by regularly adjusting the storage location of a small number of SKUs gradually, but the picker-to-parts picking system differs from the AS/RS system in the following aspects. DSLA in the picker-toparts picking systems could achieve better storage location optimization results
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