Anticipative Dynamic Slotting for Attended Home Deliveries

42 Pages Posted: 13 Apr 2019 Last revised: 30 Sep 2020

See all articles by Magdalena A.K. Lang

Magdalena A.K. Lang

RWTH Aachen University - School of Economics and Business Administration

Catherine Cleophas

CAU Kiel University

Jan Fabian Ehmke

European University Viadrina Frankfurt (Oder)

Date Written: September 30, 2020

Abstract

For attended home deliveries, customers expect narrow delivery time slots that fit their personal schedules. This severely limits the solution space for delivery planning and thereby makes attended home deliveries costly and complex for retailers. As one remedy, dynamic slotting lets the firm control the offered time slots per arriving customer. To that end, solution approaches have to quickly compare the immediate reward from accepting an order to the opportunity cost of thereby reducing the delivery capacity in the selected time slot. As the opportunity cost depend on a complex vehicle routing and scheduling problem under demand uncertainty, they are notoriously difficult to quantify.

To quickly compute good solutions, we present approaches that let an extensive, simulation-based preparation phase inform online decision making. These approaches estimate opportunity cost via approximate value function models and rely on delivery schedule anticipation. Specifically, we propose to aid the process of dynamic slotting by generating spatio-temporal delivery patterns via team orienteering on sample arrival streams.

In an extensive computational study, we compare approaches on both synthetic and empirically-validated demand scenarios. Rather than suggesting a one-size-fits-all view, we propose a differentiated set of recommendations for selecting methods dependent on the specific problem scenario. In particular, we find that benefits from relying on anticipated patterns highly depend on demand segments' basket value and location distributions.

Keywords: retail; order capture, time slot allocation; revenue management, attended home deliveries, approximate dynamic programming, team orienteering problem

Suggested Citation

Lang, Magdalena A.K. and Cleophas, Catherine and Ehmke, Jan Fabian, Anticipative Dynamic Slotting for Attended Home Deliveries (September 30, 2020). Available at SSRN: https://ssrn.com/abstract=3354537 or http://dx.doi.org/10.2139/ssrn.3354537

Magdalena A.K. Lang

RWTH Aachen University - School of Economics and Business Administration ( email )

Aachen
Germany

Catherine Cleophas (Contact Author)

CAU Kiel University ( email )

Olshausenstr. 40
Kiel, SH 24118
Germany

Jan Fabian Ehmke

European University Viadrina Frankfurt (Oder) ( email )

Grosse Scharrnstr. 59
Frankfurt (Oder), Brandenburg 15230
Germany

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
113
Abstract Views
803
rank
330,498
PlumX Metrics