Abstract
Attended home delivery (AHD) is a popular type of home delivery for which companies typically offer delivery time slots. The costs for offering time slots are often double compared to standard home delivery services (Yrjölä, 2001). To influence customers to choose a time slot that results in fewer travel costs, companies often give incentives (discounts) or penalties (delivery charges) depending on the costs of a time slot. The main focus of this paper is on determining the costs of a time slot and adjusting time slot pricing accordingly, i.e., dynamic pricing. We compare two time slot cost approximation methods, a cheapest insertion formula and a method employing random forests with a limited set of features. Our results show that time slot incentives have added value for practice. In a hypothetical situation where customers are infinitely sensitive to incentives, we can plan 6 % more customers and decrease the per-customer travel costs by 11 %. Furthermore, we show that our method works especially well when customer locations are heavily clustered or when the area of operation is sparsely populated. For a realistic case of a European e-grocery retailer, we show that we can save approximately 6 % in per-customer travel costs, and plan approximately 1 % more customers when using our time slot incentive policy.
| Original language | English |
|---|---|
| Title of host publication | Computational Logistics |
| Subtitle of host publication | 13th International Conference, ICCL 2022, Barcelona, Spain, September 21–23, 2022, Proceedings |
| Editors | Jesica de Armas, Helena Ramalhinho, Stefan Voß |
| Place of Publication | Cham |
| Publisher | Springer |
| Pages | 214–230 |
| Number of pages | 17 |
| ISBN (Electronic) | 978-3-031-16579-5 |
| ISBN (Print) | 978-3-031-16578-8 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | 13th International Conference on Computational Logistics, ICCL 2022 - Barcelona, Spain Duration: 21 Sept 2022 → 23 Sept 2022 Conference number: 13 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| Volume | 13557 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 13th International Conference on Computational Logistics, ICCL 2022 |
|---|---|
| Abbreviated title | ICCL 2022 |
| Country/Territory | Spain |
| City | Barcelona |
| Period | 21/09/22 → 23/09/22 |
Keywords
- Time slot management
- Dynamic pricing
- Vehicle routing
- Machine learning
- Cost approximation
- 22/3 OA procedure
Fingerprint
Dive into the research topics of 'Dynamic Time Slot Pricing Using Delivery Costs Approximations'. Together they form a unique fingerprint.Research output
- 4 Citations
- 1 PhD Thesis - Research UT, graduation UT
-
Machine Learning for Sequential Decisions in Logistics
Akkerman, F. R., 4 Apr 2025, Enschede, the Netherlands: University of Twente. 372 p.Research output: Thesis › PhD Thesis - Research UT, graduation UT
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