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.

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 Particle Swarm Optimization Using Neighborhood-Based Mutation Operator and Intermediate Disturbance Strategy for Outbound Container Storage Location Assignment Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yuyan He ◽  
Aihu Wang ◽  
Hailiang Su ◽  
Mengyao Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Assignment Problem ◽  
Particle Swarm ◽  
Local Solution ◽  
Mutation Operator ◽  
Swarm Optimization ◽  
Intermediate Disturbance ◽  
Storage Location ◽  
Location Assignment ◽  
Container Storage Location Assignment

Outbound container storage location assignment problem (OCSLAP) could be defined as how a series of outbound containers should be stacked in the yard according to certain assignment rules so that the outbound process could be facilitated. Considering the NP-hard nature of OCSLAP, a novel particle swarm optimization (PSO) method is proposed. The contributions of this paper could be outlined as follows: First, a neighborhood-based mutation operator is introduced to enrich the diversity of the population to strengthen the exploitation ability of the proposed algorithm. Second, a mechanism to transform the infeasible solutions into feasible ones through the lowest stack principle is proposed. Then, in the case of trapping into the local solution in the search process, an intermediate disturbance strategy is implemented to quickly jump out of the local solution, thereby enhancing the global search capability. Finally, numerical experiments have been done and the results indicate that the proposed algorithm achieves a better performance in solving OCSLAP.

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.

A Genetic Algorithm for Minimizing Relocations at Container Yard in Container Terminal

2014 ◽  
Vol 931-932 ◽  
pp. 1683-1688
Author(s):  
Phatchara Sriphrabu ◽  
Kanchana Sethanan ◽  
Somnuk Theerakulpisut
Keyword(s):  
Genetic Algorithm ◽  
Current Practice ◽  
Container Terminal ◽  
Experimental Result ◽  
Container Ship ◽  
Storage Assignment ◽  
Storage Location ◽  
Location Assignment

This paper focuses on storage location assignment and exported container relocation in container yard of container terminal with the objective of minimizing the number of container lifting. On the lifting steps, the truck with yard crane should be chosen in order to deliver a container from container yard to container ship, and this action can reduce container ship's docking time and increase effectiveness in container terminal service. In this paper, a genetic algorithm (GA) in container storage assignment and a heuristic for the container relocation determination are adopted. Also, the current practice including first-in-first-stored (FIFS) and simple relocation (SR) is used to compare the effectiveness of the GA and the proposed heuristic (RH). The experimental result presented that the proposed method is able to construct the effective solutions of storage location assignment of exported containers, and it reduces the number of relocations of exported container effectively.

scholarly journals The storage location assignment problem: A literature review

2019 ◽  
pp. 199-224 ◽  
Author(s):  
Juan José Rojas Reyes ◽  
Elyn Lizeth Solano-Charris ◽  
Jairo Rafael Montoya-Torres
Keyword(s):  
Literature Review ◽  
Assignment Problem ◽  
Storage Location ◽  
Location Assignment

A study of the sensitivity of sequence stacking strategies for the storage location assignment problem for out-bound containers in a maritime terminal

2018 ◽  
Vol 9 (5) ◽  
pp. 1057-1062
Author(s):  
Roberto Guerra-Olivares ◽  
Neale R. Smith ◽  
Rosa G. González-Ramírez ◽  
Leopoldo Eduardo Cárdenas-Barrón
Keyword(s):  
Assignment Problem ◽  
Storage Location ◽  
Location Assignment
Sign in / Sign up

Export Citation Format

Share Document