The effects of human behavior on the efficiency of routing policies in order picking: The case of route deviations

Elbert, R.; Franzke, T.; Glock, C. H.; Grosse, E. H.

doi:10.1016/j.cie.2016.11.033

Cited by 61 publications

(34 citation statements)

References 56 publications

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“…As it has been shown previously, optimal routes often seem illogical, complex or unfamiliar to human pickers (Petersen and Aase, 2004;Gademann and Velde, 2005;De Koster et al, 2007;Henn, 2012) and there is empirical knowledge that pickers deviate from them (Elbert et al, 2016). User-friendly interfaces between pickers and warehouse management systems need to be developed in order to minimise the effort needed by a picker, e.g.…”

Section: Key Findings and Discussionmentioning

confidence: 99%

“…Manual systems have been reported to reach adoption levels of 80% in the industry (De Koster et al, 2007;Napolitano, 2012). Although automating the order picking operation is feasible with today's technology, firms often choose manual solutions due to their lower cost and greater flexibility Elbert et al, 2016), leaving aside the risks associated with manual operations (Grosse et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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An interventionist strategy for warehouse order picking: Evidence from two case studies

Giannikas

Robertson

et al. 2017

International Journal of Production Economics

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As the role of the customer becomes more important in modern logistics, warehouses are required to improve their response to customer orders. To meet the responsiveness expected by customers, warehouses need to shorten completion times. In this paper, we introduce an interventionist order picking strategy that aims to improve the responsiveness of order picking systems. Unlike existing dynamic strategies, the proposed strategy allows a picker to be intervened during a pick cycle to consider new orders and operational disruptions. An interventionist strategy is compared against an existing dynamic picking strategy via a case study. We report benefits both in terms of order completion time and travel distance. This paper also introduces a set of system requirements for deploying an interventionist strategy based on a second case study.

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Section: Key Findings and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An interventionist strategy for warehouse order picking: Evidence from two case studies

Giannikas

Robertson

et al. 2017

International Journal of Production Economics

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“…Zulj et al [17] proposed a model allowing the identification of a picking-routing strategy based on stacking constraints. The effects of the human behavior on the efficiency of routing policies in order picking are investigated in [26]. The study is focused on how deviations from routes impact the efficiency of different routing policies.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The objective in (12) is minimizing the total cost, which is the sum of the penalty cost related to makespan over all of the jobs (weighted by π I ), the penalty cost related to the completion time of the overall battery recharging process (weighted by π II ), and the total electricity cost for charging batteries of forklifts (weighted by π III ). Constraints (13)- (16) are related to the job scheduling, whilst (17)- (26) and 27- (36) are aimed at scheduling the optimal battery changes and determining the optimal recharging cost strategies, respectively. Finally, Constraints (37)-(40) specify the integrality conditions on the defined decision variables.…”

Section: Second-step Optimizationmentioning

confidence: 99%

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Sustainable Scheduling of Material Handling Activities in Labor-Intensive Warehouses: A Decision and Control Model

et al. 2020

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In recent years, the continuous increase of greenhouse gas emissions has led many companies to investigate the activities that have the greatest impact on the environment. Recent studies estimate that around 10% of worldwide CO2 emissions derive from logistical supply chains. The considerable amount of energy required for heating, cooling, and lighting as well as material handling equipment (MHE) in warehouses represents about 20% of the overall logistical costs. The reduction of warehouses’ energy consumption would thus lead to a significant benefit from an environmental point of view. In this context, sustainable strategies allowing the minimization of the cost of energy consumption due to MHE represent a new challenge in warehouse management. Consistent with this purpose, a two-step optimization model based on integer programming is developed in this paper to automatically identify an optimal schedule of the material handling activities of electric mobile MHEs (MMHEs) (i.e., forklifts) in labor-intensive warehouses from profit and sustainability perspectives. The resulting scheduling aims at minimizing the total cost, which is the sum of the penalty cost related to the makespan of the material handling activities and the total electricity cost of charging batteries. The approach ensures that jobs are executed in accordance with priority queuing and that the completion time of battery recharging is minimized. Realistic numerical experiments are conducted to evaluate the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. The obtained results show the effectiveness of the model in identifying the optimal battery-charging schedule for a fleet of electric MMHEs from economic and environmental perspectives simultaneously.

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A Diagnostic Model for Determining the Reasons Causing Low Quality Logistics Services in SME Logistics Operators

Vega-Barros

Palomino-Ruiz

Leon-Chavarri

et al. 2021

Proceedings of the 6th Brazilian Technology Symposium (BTSym’20)

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The effects of human behavior on the efficiency of routing policies in order picking: The case of route deviations

Cited by 61 publications

References 56 publications

An interventionist strategy for warehouse order picking: Evidence from two case studies

An interventionist strategy for warehouse order picking: Evidence from two case studies

Sustainable Scheduling of Material Handling Activities in Labor-Intensive Warehouses: A Decision and Control Model

A Diagnostic Model for Determining the Reasons Causing Low Quality Logistics Services in SME Logistics Operators

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