scholarly journals Optimization of the Storage Location Assignment and the Picker-Routing Problem by Using Mathematical Programming

2020 ◽  
Vol 10 (2) ◽  
pp. 534 ◽  
Author(s):  
Johanna Bolaños Zuñiga ◽  
Jania Astrid Saucedo Martínez ◽  
Tomas Eloy Salais Fierro ◽  
José Antonio Marmolejo Saucedo
Keyword(s):  
Order Picking ◽  
Routing Problem ◽  
On Demand ◽  
Similar Work ◽  
Routing Policy ◽  
Storage Location ◽  
Location Assignment ◽  
Product Weight ◽  
Selection Of

The order picking process involves a series of activities in response to customer needs, such as the selection or programming of orders (batches), and the selection of different items from their storage location to shipment. These activities are accomplished by a routing policy that determines the picker sequence for retrieving the items from the storage location. Therefore, the order picking problem has been plenty investigated; however, in previous research, the proposed models were based on demand fulfilling, putting aside factors such as the product weight—which is an important criterion—at the time of establishing routes. In this article, a mathematical model is proposed; it takes into account the product’s weight derived from a case study. This model is relevant, as no similar work was found in the literature that improves the order picking by making simultaneous decisions on the storage location assignment and the picker-routing problem, considering precedence constraints based on the product weight and the characteristics of the case study, as the only location for each product in a warehouse with a general layout.

Constrained clustering method for class-based storage location assignment in warehouse

2016 ◽  
Vol 116 (4) ◽  
pp. 667-689 ◽  
Author(s):  
Chao-Lung Yang ◽  
Thi Phuong Quyen Nguyen
Keyword(s):  
Principal Component ◽  
Constrained Clustering ◽  
Clustering Method ◽  
Content Type ◽  
Assignment Model ◽  
Retrieval Efficiency ◽  
Storage Location ◽  
Component Loadings ◽  
Location Assignment

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.

scholarly journals Using the Efficient Frontier to Obtain the Best Solution for the Storage Location Assignment Problem

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Marcele Elisa Fontana ◽  
Cristiano Alexandre Virgínio Cavalcante
Keyword(s):  
Assignment Problem ◽  
Efficient Frontier ◽  
Order Picking ◽  
Total Order ◽  
Pareto Optimal ◽  
Storage Process ◽  
Use Of Space ◽  
Storage Location ◽  
Location Assignment ◽  
And Storage

The main variables that influence the efficiency of a warehouse are the use of space and the order picking distance. In the literature, there are proposals to add the costs with space and order picking in order to evaluate each alternative for storage location assignment. However, there were problems with the adoption of this methodology, including difficulties in determining the costs and tradeoffs between them. These difficulties can result in solutions that are suboptimal. Based on these facts, this paper proposes a class-based storage process and storage location assignment by a cube-per-order index (COI) that analyzes the space required and the total order picking distance by Pareto-optimal calculations. The efficient frontier possibilities allow the reduction of the set of alternatives, and the DM can analyze only the alternatives on efficient frontier.

scholarly journals Collaborative Optimization of Storage Location Assignment and Path Planning in Robotic Mobile Fulfillment Systems

2021 ◽  
Vol 13 (10) ◽  
pp. 5644
Author(s):  
Jianming Cai ◽  
Xiaokang Li ◽  
Yue Liang ◽  
Shan Ouyang
Keyword(s):  
Path Planning ◽  
Green Technology ◽  
Order Picking ◽  
Collaborative Optimization ◽  
A Algorithm ◽  
Logistics Industry ◽  
Operation Rules ◽  
Storage Location ◽  
Assignment Strategy ◽  
Location Assignment

The robotic mobile fulfillment system (RMFS) is a new automatic warehousing system, a type of green technology, and an emerging trend in the logistics industry. In this study, we take an RMFS as the research object and combine the connected issues of storage location assignment and path planning into one optimization problem from the perspective of collaborative optimization. A sustainable mathematical model for the collaborative optimization of storage location assignment and path planning (COSLAPP) is established, which considers the relationship between the location assignment of goods and rack storage and path planning in an RMFS. On this basis, we propose a location assignment strategy for goods clustering and rack turnover, which utilizes reservation tables, sets AGV operation rules to resolve AGV running conflicts, and improves the A-star(A*) algorithm based on the node load to find the shortest path by which the AGV handling the racks can complete the order picking. Ultimately, simulation studies were performed to ascertain the effectiveness of COSLAPP in the RMFS; the results show that the new approach can significantly improve order picking efficiency, reduce energy consumption, and lessen the operating costs of the warehouse of a distribution center.

scholarly journals Defining a storage-assignment strategy for precedence-constrained order picking

2021 ◽  
Vol 31 (2) ◽  
Author(s):  
Maria A. M. Trindade ◽  
Paulo S. A. Sousa ◽  
Maria R. A. Moreira
Keyword(s):  
Assignment Problem ◽  
Real Life ◽  
Order Picking ◽  
Quadratic Assignment ◽  
Assignment Model ◽  
Storage Assignment ◽  
Storage Location ◽  
Assignment Strategy ◽  
Location Assignment ◽  
The Creation

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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