An integrated storage assignment method for manual order picking warehouses considering cost, workload and posture

2018 ◽  
Vol 57 (8) ◽  
pp. 2392-2408 ◽  
Author(s):  
Martina Calzavara ◽  
Christoph H. Glock ◽  
Eric H. Grosse ◽  
Fabio Sgarbossa
Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ruiping Yuan ◽  
Juntao Li ◽  
Wei Wang ◽  
Jiangtao Dou ◽  
Luke Pan

Robotic mobile fulfillment system (RMFS) is a new type of parts-to-picker order picking system, where robots carry inventory pods to stationary pickers. Because of the difference in working mode, traditional storage assignment methods are not suitable for this new kind of picking system. This paper studies the storage assignment optimization of RMFS, which is divided into products assignment stage and pods assignment stage. In the products assignment stage, a mathematical model maximizing the total correlation of products in the same pods is established to reduce the times of pod visits, and a scattered storage policy is adopted to reduce system congestion. A heuristic algorithm is designed to solve the model. In the pods assignment stage, a model is established minimizing the total picking distance of the mobile robots considering the turnover rate and the correlation of pods as well as the workload balance among picking corridors. A two-stage hybrid algorithm combining greedy algorithm and improved simulated annealing is designed to solve the model. Finally, a simulation experiment is carried out based on the historical order data of an e-commerce company. Results show that the storage assignment method proposed in the paper significantly improves the efficiency of order picking.


2018 ◽  
Vol 9 (2) ◽  
pp. 37-45
Author(s):  
Jakob Marolt ◽  
Tone Lerher

Abstract Our research objective is to lower intralogistics costs by minimizing the number of shuffling operations in a steel plant company commercial warehouse. The process of dispatching products consists of retrieving set of steel bar (SSB) from a floor stored stack or a special stacking frame by an overhead crane. To retrieve a targeted merchandise all SSB above targeted must be reshuffled. Proper assignment of storage locations is a key logistics problem for efficient order picking. We are comparing two heuristics, that do not require information of dispatching sequence of any stored products. We simulated the problem at hand with both methods. Our objective is to count the number of reshuffles using each heuristic on randomly generated examples and decide which is better in the long run. Our problem has similarities with storage assignment of steel plates or steel coils for minimization of reshuffling operations. The problem is also comparable to storage assignment of containers in a container yard. In our case we are dealing with a special stacking configuration of products, that demands different approach. We want to demonstrate which heuristic should be used in companies that lack necessary storage information infrastructure.


2019 ◽  
Vol 58 (22) ◽  
pp. 6949-6969
Author(s):  
David Revillot-Narváez ◽  
Francisco Pérez-Galarce ◽  
Eduardo Álvarez-Miranda

2014 ◽  
Vol 28 (1) ◽  
pp. 111-129 ◽  
Author(s):  
K. L. Choy ◽  
G. T. S. Ho ◽  
C. K. H. Lee

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.


2017 ◽  
Vol 28 (3) ◽  
pp. 841-863 ◽  
Author(s):  
Torsten Franzke ◽  
Eric H. Grosse ◽  
Christoph H. Glock ◽  
Ralf Elbert

Purpose Order picking is one of the most costly logistics processes in warehouses. As a result, the optimization of order picking processes has received an increased attention in recent years. One potential source for improving order picking is the reduction of picker blocking. The purpose of this paper is to investigate picker blocking under different storage assignment and order picker-route combinations and evaluate its effects on the performance of manual order picking processes. Design/methodology/approach This study develops an agent-based simulation model (ABS) for order picking in a rectangular warehouse. By employing an ABS, we are able to study the behaviour of individual order pickers and their interactions with the environment. Findings The simulation model determines shortest mean throughput times when the same routing policy is assigned to all order pickers. In addition, it evaluates the efficiency of alternative routing policies–storage assignment combinations. Research limitations/implications The paper implies that ABS is well-suited for further investigations in the field of picker blocking, for example, with respect to the individual behaviour of agents. Practical implications Based on the results of this paper, warehouse managers can choose an appropriate routing policy that best matches their storage assignment policy and the number of order pickers employed. Originality/value This paper is the first to comprehensively study the effects of different combinations of order picker routing and storage assignment policies on the occurrence of picker blocking.


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