A dynamic storage location assignment model for a progressive bypass zone picking system with an S/R crane

Author(s):  
Jeonghwan Kim ◽  
Soondo Hong
2016 ◽  
Vol 116 (4) ◽  
pp. 667-689 ◽  
Author(s):  
Chao-Lung Yang ◽  
Thi Phuong Quyen Nguyen

Purpose – Class-based storage has been studied extensively and proved to be an efficient storage policy. However, few literature addressed how to cluster stuck items for class-based storage. The purpose of this paper is to develop a constrained clustering method integrated with principal component analysis (PCA) to meet the need of clustering stored items with the consideration of practical storage constraints. Design/methodology/approach – In order to consider item characteristic and the associated storage restrictions, the must-link and cannot-link constraints were constructed to meet the storage requirement. The cube-per-order index (COI) which has been used for location assignment in class-based warehouse was analyzed by PCA. The proposed constrained clustering method utilizes the principal component loadings as item sub-group features to identify COI distribution of item sub-groups. The clustering results are then used for allocating storage by using the heuristic assignment model based on COI. Findings – The clustering result showed that the proposed method was able to provide better compactness among item clusters. The simulated result also shows the new location assignment by the proposed method was able to improve the retrieval efficiency by 33 percent. Practical implications – While number of items in warehouse is tremendously large, the human intervention on revealing storage constraints is going to be impossible. The developed method can be easily fit in to solve the problem no matter what the size of the data is. Originality/value – The case study demonstrated an example of practical location assignment problem with constraints. This paper also sheds a light on developing a data clustering method which can be directly applied on solving the practical data analysis issues.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xiangbin Xu ◽  
Chenhao Ren

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.


2021 ◽  
Vol 31 (2) ◽  
Author(s):  
Maria A. M. Trindade ◽  
Paulo S. A. Sousa ◽  
Maria R. A. Moreira

This paper proposes a zero-one quadratic assignment model for dealing with the storage location assignment problem when there are weight constraints. Our analysis shows that operations can be improved using our model. When comparing the strategy currently used in a real-life company with the designed model, we found that the new placement of products allowed a reduction of up to 22% on the picking distance. This saving is higher than that achieved with the creation of density zones, a procedure commonly used to deal with weight constraints, according to the literature.


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