research-article
Authors: Uta Mohring, Christoph Jacobi, Kai Furmans, and Raik Stolletz
Published: 03 January 2024 Publication History
- 0citation
- 0
- Downloads
Metrics
Total Citations0Total Downloads0Last 12 Months0
Last 6 weeks0
New Citation Alert added!
This alert has been successfully added and will be sent to:
You will be notified whenever a record that you have chosen has been cited.
To manage your alert preferences, click on the button below.
Manage my Alerts
New Citation Alert!
Please log in to your account
- View Options
- References
- Media
- Tables
- Share
Abstract
Warehouses recently face increasing stress imposed by a volatile customer demand and increasing customer expectations in terms of ever shorter order response times. In that respect, warehouses more and more offer same-day and next-day shipment conditions. However, same-day shipment promises are challenging to fulfil, especially as the order fulfilment process operates against fixed deadlines imposed by the predefined truck departure times. As a natural mitigation strategy, warehouses set a cutoff point and offer same-day shipment only to customers that order until the cutoff point, but next-day shipment to all customers ordering thereafter. Setting an appropriate cutoff point is challenging as it affects multiple facets of the service quality, such as the order response time and the service level. In this paper, we study the design of cutoff-based shipment promises for stochastic deadline-oriented order fulfilment processes in warehouses. We present a discrete-time Markov chain model for exact steady-state performance analysis and propose two novel performance measures – and cutoff service level – for service level measurement in these systems. We numerically show the benefit of cutoff-based shipment promises. Even with a late cutoff point, there is a significant gain in the system performance. Furthermore, we find that warehouses should set the cutoff point such that it balances customer expectations in terms of service level and order response time. Finally, warehouses can improve their shipment promises when referring to instead of cutoff service level and by implementing measures reducing the utilisation and the variabilities of the order fulfilment process.
References
[1]
Boysen N, de Koster R, and Füßler D The forgotten sons: warehousing systems for brick-and-mortar retail chains Eur J Oper Res 2021 288 2 361-381
[2]
Boysen N, de Koster R, and Weidinger F Warehousing in the e-commerce era: a survey Eur J Oper Res 2019 277 2 396-411
[3]
Boysen N, Schwerdfeger S, and Stephan K A review of synchronization problems in parts-to-picker warehouses Eur J Oper Res 2023 307 3 1374-1390
[4]
Ceven E and Gue K Optimal wave release times for order fulfilment systems with deadlines Transp Sci 2017 51 1 52-66
Digital Library
[5]
Chen TL, Cheng CY, Chen YY, and Chan LK An efficient hybrid algorithm for integrated order batching, sequencing and routing problem Int J Prod Econ 2015 159 158-167
[6]
Chew EP and Tang LC Travel time analysis for general item location assignment in a rectangular warehouse Eur J Oper Res 1999 112 3 582-597
[7]
de Koster R, Le-Duc T, and Roodbergen KJ Design and control of warehouse order picking: a literature review Eur J Oper Res 2007 182 2 481-501
[8]
Doerr K and Gue K A performance metric and goal-setting procedure for deadline-oriented processes Prod Oper Manag 2013 22 3 726-738
[9]
Henn S and Schmid V Metaheuristics for order batching and sequencing in manual order picking systems Comput Ind Eng 2013 66 2 338-351
Digital Library
[10]
Kim TY Improving warehouse responsiveness by job priority management: A european distribution centre field study Comput Ind Eng 2020 139
Digital Library
[11]
Klapp M, Erera A, and Toriello A The dynamic dispatch waves problem for same-day delivery Eur J Oper Res 2018 271 2 519-534
[12]
Law AM Simulation modelling and analysis 2015 5 New York McGraw-Hill Education
[13]
Le-Duc T and de Koster RM Travel time estimation and order batching in a 2-block warehouse Eur J Oper Res 2007 176 1 374-388
[14]
MacCarthy B, Zhang L, and Muyldermans L Best performance frontiers for buy-online-pickup-in-store order fulfilment Int J Prod Econ 2019 211 251-264
[15]
Menéndez B, Bustillo M, Pardo EG, and Duarte A General variable neighbourhood search for the order batching and sequencing problem Eur J Oper Res 2017 263 1 82-93
[16]
Mohring U, Baumann M, and Furmans K Discrete-time analysis of levelled order release and staffing in order picking systems Logist Res 2020
[17]
Schleyer M and Gue K Throughput time distribution analysis for a one-block warehouse Transport Res Part E Logist Transport Rev 2012 48 3 652-666
[18]
Scholz A, Schubert D, and Wäscher G Order picking with multiple pickers and due dates-simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems Eur J Oper Res 2017 263 2 461-478
[19]
Tempelmeier H Inventory management in supply networks: problems, models, solutions 2011 2 Norderstedt Books on Demand
[20]
Ulmer M Dynamic pricing and routing for same-day delivery Transport Sci 2020 54 4 1016-1033
Digital Library
[21]
van Gils T, Ramaekers K, Caris A, and Cools M The use of time series forecasting in zone order picking systems to predict order pickers’ workload Int J Prod Res 2017 55 21 6380-6393
[22]
van Gils T, Ramaekers K, Caris A, and de Koster RB Designing efficient order picking systems by combining planning problems: state-of-the-art classification and review Eur J Oper Res 2018 267 1 1-15
[23]
van Nieuwenhuyse I and de Koster RB Evaluating order throughput time in 2-block warehouses with time window batching Int J Prod Econ 2009 121 2 654-664
[24]
Vanheusden S, van Gils T, Braekers K, Ramaekers K, and Caris A Analysing the effectiveness of workload balancing measures in order picking operations Int J Prod Res 2021 60 7 2126-2150
[25]
Vanheusden S, van Gils T, Caris A, Ramaekers K, and Braekers K Operational workload balancing in manual order picking Comput Ind Eng 2020 141
Digital Library
[26]
Voccia S, Campbell A, and Thomas B The same-day delivery problem for online purchases Transport Sci 2019 53 1 167-184
Digital Library
[27]
Xu X, Liu T, Li K, and Dong W Evaluating order throughput time with variable time window batching Int J Prod Res 2014 52 8 2232-2242
[28]
Yaman H, Karasan OE, and Kara BY Release time scheduling and hub location for next-day delivery Oper Res 2012 60 4 906-917
Digital Library
[29]
Zhang J, Wang X, and Huang K Integrated on-line scheduling of order batching and delivery under B2C e-commerce Comput Ind Eng 2016 94 280-289
Digital Library
Recommendations
- Lot sizing and unequal-sized shipment policy for an integrated production-inventory system
This article develops a single-manufacturer single-retailer production-inventory model in which the manufacturer delivers the retailer’s ordered quantity in unequal shipments. The manufacturer’s production process is imperfect and it may produce some ...
Read More
- Uncovering Critical Products in Retail Baskets: A Predictive Modelling Approach to Increase Order Fulfilment
AIMLSystems '23: Proceedings of the Third International Conference on AI-ML Systems
Order fulfilment is a key goal for retailers. It is impacted by item unavailability, poor item quality and delivery mishaps. Although the north star is to resolve these challenges completely, in practice, retailers would benefit by prioritizing perfect ...
Read More
- A B2C e-commerce intelligent system for re-engineering the e-order fulfilment process
The e-commerce internal order processing flow is streamlined and re-designed.A GA-rule-based system for efficient e-commerce order fulfilment is proposed.An optimal order processing plan is generated by genetic algorithm technique.A system ...
Read More
Comments
Information & Contributors
Information
Published In
OR Spectrum Volume 46, Issue 2
Jun 2024
396 pages
ISSN:0171-6468
Issue’s Table of Contents
© The Author(s) 2024.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 03 January 2024
Accepted: 20 November 2023
Received: 01 October 2022
Author Tags
- Order fulfilment
- Deadline
- Service level
- Shipment
- Markov chain
Qualifiers
- Research-article
Funding Sources
- Deutsche Forschungsgemeinschaft
- Karlsruher Institut für Technologie (KIT) (4220)
Contributors
Other Metrics
View Article Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
Total Citations
Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Other Metrics
View Author Metrics
Citations
View Options
View options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in
Full Access
Get this Publication
Media
Figures
Other
Tables
View Issue’s Table of Contents
