order picking
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2021 ◽  
Vol 20 (4) ◽  
pp. 719-729
Author(s):  
B. Gajsek ◽  
G. Dukic ◽  
M. Kovacic ◽  
M. Brezocnik

2021 ◽  
Vol 24 ◽  
pp. 60-67
Author(s):  
Gerrit Karel Janssens ◽  
Stef Moons ◽  
Katrien Ramaekers ◽  
An Caris

In a business-to-consumer (B2C) context, customers order more frequently and in smaller quantities, resulting in a high number of consignments. Moreover, online shoppers expect a fast and accurate delivery at low cost or even free. To survive in such a market, companies can no longer optimise individual supply chain processes, but need to integrate several activities. In this article, the integrated order picking-vehicle routing problem is analysed in an e-commerce environment. In previous research, a mathematical programming formulation has been formulated in literature but only small-size instances can be solved to optimality. Two picking policies are studied: discrete order picking and batch order picking. The influence of various problem contexts on the value of integration is investigated: a small picking time period, outsourcing to 3PL service providers, and a dynamic environment context.


2021 ◽  
Vol 13 (23) ◽  
pp. 13374
Author(s):  
Anna Cierniak-Emerych ◽  
Robert Golej ◽  
Hanna Różycka

The research presented herein aims to pinpoint the factors that cause errors in the order picking process in an e-commerce enterprise and to confirm or deny the assumption that these factors largely concern employees and their working conditions. Research method: A case study strategy, observation (non-compliance cards and identification of working conditions), and Lorenz–Pareto and Ishikawa were the methods used. Results: The research results indicate that working conditions are a key factor influencing the number of errors in the picking process. The usefulness of the research: The results show that paying particular attention to working conditions is not only good in the context of caring for the well-being of employees, but also as a means to reduce the number of errors and improve the pace of work. Limitations: Due to the methods used, which in turn result from the large variety of e-commerce entities, the research results are not universal and are limited to a specific situational context.


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.


Author(s):  
XiaoLi Zhang ◽  
Jelle Vries ◽  
René Koster ◽  
ChenGuang Liu

2021 ◽  
pp. 800-811
Author(s):  
Bensu Güntez ◽  
Gizem İşgüzerer ◽  
Çağla Güşeç ◽  
Merve Özen ◽  
Mert Paldrak ◽  
...  
Keyword(s):  

2021 ◽  
pp. 401-412
Author(s):  
Edin Sancaklı ◽  
İrem Dumlupınar ◽  
Ali Osman Akçın ◽  
Ezgi Çınar ◽  
İpek Geylani ◽  
...  

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