An agent-based modeling approach to analyze the impact of warehouse congestion on cost and performance

Heath, Brian L.; Ciarallo, Frank W.; Hill, Raymond R.

doi:10.1007/s00170-012-4505-5

Cited by 20 publications

(9 citation statements)

References 14 publications

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“…The proposed algorithm can be extended to the case of more than two order pickers (Chen et al , 2014). Heath et al (2013) employed an ABS and showed that extra travel time caused by picker blocking is one of the most important drivers of total order processing time. The authors modelled random and a modified s-shape routing as well as random and turnover-based storage assignment.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Investigating the causes and consequences of picker blocking in real-world environments is often very difficult due to the many factors that could influence picker blocking – traffic or possibly the unnoticed decisions of order pickers, especially if several blocking situations occur at the same time, to name just two examples. Quantifying the effects of picker blocking on warehouse efficiency based on practical observations involves the risk that important influencing factors or consequences are ignored or misinterpreted (Heath et al , 2013). Developing analytical models is a possible remedy to this problem.…”

Section: Simulation Studymentioning

confidence: 99%

“…Picker blocking can result in longer travel times due to idle or waiting times, and hence may reduce order picking efficiency (Chen et al , 2013, 2014; Mowrey and Parikh, 2014; Parikh and Meller, 2008). Due to the complex and stochastic nature of picker blocking, its influence on the performance of order picking is difficult to quantify (Heath et al , 2013).…”

Section: Introductionmentioning

confidence: 99%

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An investigation of the effects of storage assignment and picker routing on the occurrence of picker blocking in manual picker-to-parts warehouses

Franzke

Grosse

Glock

et al. 2017

IJLM

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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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Section: Literature Reviewmentioning

confidence: 99%

Section: Simulation Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An investigation of the effects of storage assignment and picker routing on the occurrence of picker blocking in manual picker-to-parts warehouses

Franzke

Grosse

Glock

et al. 2017

IJLM

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“…Second, the typical linear distance-time relation strongly simplifies the real behaviour of pick vehicles. Pick vehicle acceleration and deceleration (Heath, Ciarallo, and Hill 2013), as well as making left-, right-, U-turns and driving backwards at a slower pace (C ¸elik and Süral 2016) is expected to substantially affect travel time and consequently order picking efficiency (Wen, Chang, and Chen 2001).…”

Section: Pick Vehicle Propertiesmentioning

confidence: 99%

Practical factors in order picking planning: state-of-the-art classification and review

Vanheusden

Gils

Ramaekers

et al. 2022

International Journal of Production Research

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Market trends such as globalisation, increasing customer expectations, expensive industrial land and high labour costs cause a need for efficient order picking systems in practice. However, managers often do not implement findings from academic research on order picking planning into practice because researchers hardly account for practical factors (e.g., high-level storage, human factors, pick vehicle properties) or make unrealistic assumptions in their solution algorithms. A state-of-the-art review of the scientific literature on order picking planning (1) identifies and classifies highly influential practical factors, (2) shows the impact of these practical factors on order picking performance, and (3) illustrates how existing order picking planning models should be elaborated to account for practical factors. This study contributes to close the gap between research and practice by guiding future researchers to further increase the practical applicability of their research results.

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“…Similarly, to discrete-event simulation, ABSM nds application in warehouses and logistics context. It has been demonstrated the ability of ABSM to support the understanding and quanti cation of congestion in a warehouse order picker system, providing more general insights than attainable using other modeling paradigms [34]. This approach has also been employed to evaluate the performance of a mini-load multishuttle order picking system, composed of a storage area, picking workstations and a loop conveyor to transport the product totes between the storage area and workstations [12].…”

Section: Research Background and Contributionmentioning

confidence: 99%

An integrated simulation modelling approach for a warehouse 4.0

Ferrari¹,

Zenezini²,

Carlin³

et al. 2021

Preprint

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In a progressively unstable business environment characterized by customers' demand challenging to predict, innovative solutions must be developed to respond to the growing need for flexibility in supply chain operations. In this scenario, the innovations of Industry 4.0 allow exploiting new methods for the development, management, and improvement of processes. Supply chain operations can significantly benefit from implementing one of these innovations, namely Warehouse automation, which is composed of automated retrieval and storage systems (AS/RS) and mobile robots (MR). This article contributes provides a hybrid virtual model based on Agent-Based Modeling and Simulation (ABMS) and Discrete Event Simulation (DES) paradigms of an integrated warehouse system, aiming to an ex-ante evaluation of the level of performance of the various logistic flows and the impact of operating parameters. The system into analysis consists of an automated warehouse with a maxi-shuttle-type translator, enslaved by mobile industrial robots and interfaced with a laboratory factory system equipped with an assembly station. Four experiments are carried out to analyze the warehousing system's performance by varying different parameters and design configurations. Results show that the model can determine the best design trade-off in terms of performance and is able to identify the bottlenecks of the system.

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An agent-based modeling approach to analyze the impact of warehouse congestion on cost and performance

Cited by 20 publications

References 14 publications

An investigation of the effects of storage assignment and picker routing on the occurrence of picker blocking in manual picker-to-parts warehouses

An investigation of the effects of storage assignment and picker routing on the occurrence of picker blocking in manual picker-to-parts warehouses

Practical factors in order picking planning: state-of-the-art classification and review

An integrated simulation modelling approach for a warehouse 4.0

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