Storage location assignment: Using the product structure to reduce order picking times

1996 ◽  
Vol 46-47 ◽  
pp. 595-603 ◽  
Author(s):  
H. Brynzér ◽  
M.I. Johansson
Keyword(s):  
Product Structure ◽  
Order Picking ◽  
Storage Location ◽  
Location Assignment

scholarly journals Data driven storage location assignment problem considering order picking frequencies: A heuristic approach

2021 ◽  
Vol 27 (4) ◽  
pp. 520-531
Author(s):  
İpek Çobanoğlu ◽  
İrem Güre ◽  
Vedat Bayram
Keyword(s):  
Assignment Problem ◽  
Order Picking ◽  
Heuristic Approach ◽  
Data Driven ◽  
Storage Location ◽  
Location Assignment

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 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.

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.

Improving order-picking operation through efficient storage location assignment: A new approach

2020 ◽  
Vol 139 ◽  
pp. 106186 ◽  
Author(s):  
Meng Wang ◽  
Ren-Qian Zhang ◽  
Kun Fan
Keyword(s):  
Order Picking ◽  
New Approach ◽  
Efficient Storage ◽  
Storage Location ◽  
Location Assignment

scholarly journals Improving Order-picking Operations with Precedence Constraints through Efficient Storage Location Assignment

2021 ◽  
Vol 7 (3) ◽  
pp. 34-52
Author(s):  
Maria Trindade ◽  
Paulo Sousa ◽  
Maria Moreira
Keyword(s):  
Similarity Index ◽  
Order Picking ◽  
Storage Allocation ◽  
Alternative Clustering ◽  
Efficient Storage ◽  
Storage Location ◽  
Location Assignment ◽  
The One ◽  
Retail Company ◽  
Clustering Similarity

This paper is inspired by a manual picking retail company where shape and weight constraints affect the order-picking process. We proposed an alternative clustering similarity index that considers the similarity, the weight and the shape of products. This similarity index was further incorporated in a storage allocation heuristic procedure to set the location of the products. We test the procedure in a retail company that supplies over 191 stores, in Northern Portugal. When comparing the strategy currently used in the company with this procedure, we found out that our approach enabled a reduction of up to 40% on the picking distance; a percentage of improvement that is 32% higher than the one achieved by applying the Jaccard index, a similarity index commonly used in the literature. This allows warehouses to save time and work faster.

Model for Order-Batching with Congestion Consideration

2017 ◽  
Vol 64 (2) ◽  
pp. 193-212
Author(s):  
Grzegorz Tarczyński
Keyword(s):  
Probability Distributions ◽  
Analytical Form ◽  
Optimal Number ◽  
Order Picking ◽  
Average Order ◽  
Order Batching ◽  
Abc Classification ◽  
Routing Heuristics ◽  
Storage Location ◽  
Location Assignment

The paper presents the model for optimal number of merged orders that will reduce the average order-picking time. Two order batching policies were described: pick-then-sort and sort-while-pick. One-block rectangular warehouses were considered. The author studied two routing heuristics: s-shape and return for which the equations for average order-picking time can be designated based on probability distributions: binomial distribution and uniform distribution. The research takes into account the possible congestion problem. Based on simulations the analytical form of blocking time for pickers was proposed. The study shows that the advantages of each additional merged order is getting smaller. Using ABC classification for storage location assignment in warehouses with low number of aisles and large pick lists can extend the average order-picking time.

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