Ergonomic and economic optimization of layout and item assignment of a U-shaped order picking zone

Diefenbach, Heiko; Glock, C. H.

doi:10.1016/j.cie.2019.106094

Cited by 38 publications

(30 citation statements)

References 60 publications

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“…After optimization, the total time to complete the material picking process is 9:31, which represents a significant saving compared to the original time of 10:20. The optimal storage of material items in shelving positions according to categories is 17,19,18,14,6,27,3,32,8,1,28,22,7,33,29,5,21,26,15,13,16,11,25,23,34,10,9,20,2,24,12,31,30,4. In this order, the individual categories of material items should be placed in the racking positions.…”

Section: Resultsmentioning

confidence: 99%

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The Use of a Simulation Model for High-Runner Strategy Implementation in Warehouse Logistics

2020

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This paper examines the use of computer simulation methods to streamline the process of picking materials within warehouse logistics. The article describes the use of a genetic algorithm to optimize the storage of materials in shelving positions, in accordance with the method of High-Runner Strategy. The goal is to minimize the time needed for picking. The presented procedure enables the creation of a software tool in the form of an optimization model that can be used for the needs of the optimization of warehouse logistics processes within various types of production processes. There is a defined optimization problem in the form of a resistance function, which is of general validity. The optimization is represented using the example of 400 types of material items in 34 categories, stored in six rack rows. Using a simulation model, a comparison of a normal and an optimized state is realized, while a time saving of 48 min 36 s is achieved. The mentioned saving was achieved within one working day. However, the application of an approach based on the use of optimization using a genetic algorithm is not limited by the number of material items or the number of categories and shelves. The acquired knowledge demonstrates the application possibilities of the genetic algorithm method, even for the lowest levels of enterprise logistics, where the application of this approach is not yet a matter of course but, rather, a rarity.

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Section: Resultsmentioning

confidence: 99%

“…Another area of warehouse logistics that significantly affects the efficiency of processes within the warehouse is picking [14]. Picking not only affects warehousing but also affects other logistics processes within production and production.…”

Section: Introductionmentioning

confidence: 99%

The Use of a Simulation Model for High-Runner Strategy Implementation in Warehouse Logistics

2020

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“…However, alternative layouts for order picking areas are quite common in practice. These include U-shaped layouts, where shelves or pallets are arranged in the shape of a U within the order picking area (Glock and Grosse 2012;Diefenbach and Glock 2019). We note that Henn et al (2013) also refer to their considered layout as U-shaped.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The layout of an instance is defined by setting n and m, the number of stillages in one horizontal and in one vertical row. Since both Glock and Grosse (2012) and Diefenbach and Glock (2019) found that narrow U-shapes are advantageous, we consider the layouts of (n, m) = ( 10 In accordance with Glock and Grosse (2012), we set the measurements of the stillages to w = 1.3 m and the gap between the stillages to s = 0.05 m.…”

Section: Generating Instances For the Computational Testsmentioning

confidence: 99%

“…Given the special structure of the pick zone, the authors used a simple sweep algorithm to solve the routing problem. Diefenbach and Glock (2019) also studied a U-shaped warehouse and optimized the layout and item assignment for single command picking with regard to two different objectives, namely pick efficiency and ergonomics. They did, however, not study the routing problem since it is not relevant for single command picking.…”

Section: Introductionmentioning

confidence: 99%

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New solution procedures for the order picker routing problem in U-shaped pick areas with a movable depot

et al. 2021

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This paper develops new solution procedures for the order picker routing problem in U-shaped order picking zones with a movable depot, which has so far only been solved using simple heuristics. The paper presents the first exact solution approach, based on combinatorial Benders decomposition, as well as a heuristic approach based on dynamic programming that extends the idea of the venerable sweep algorithm. In a computational study, we demonstrate that the exact approach can solve small instances well, while the heuristic dynamic programming approach is fast and exhibits an average optimality gap close to zero in all test instances. Moreover, we investigate the influence of various storage assignment policies from the literature and compare them to a newly derived policy that is shown to be advantageous under certain circumstances. Secondly, we investigate the effects of having a movable depot compared to a fixed one and the influence of the effort to move the depot.

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The Impact of the Design Decisions of an Order Picking System on Human Factors Aspects of the Order Pickers

Vijayakumar,

Sgarbossa

2023

IFIP Advances in Information and Communication Technology

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Ergonomic and economic optimization of layout and item assignment of a U-shaped order picking zone

Cited by 38 publications

References 60 publications

The Use of a Simulation Model for High-Runner Strategy Implementation in Warehouse Logistics

The Use of a Simulation Model for High-Runner Strategy Implementation in Warehouse Logistics

New solution procedures for the order picker routing problem in U-shaped pick areas with a movable depot

The Impact of the Design Decisions of an Order Picking System on Human Factors Aspects of the Order Pickers

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