Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence

Sami Serkan Özarık; Lucas P. Veelenturf; Tom Van Woensel; Gilbert Laporte

doi:10.1016/j.tre.2021.102263

Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence

Sami Serkan Özarık, Lucas P. Veelenturf, Tom Van Woensel, Gilbert Laporte

Research output: Contribution to journal › Article › peer-review

56 Citations (SciVal)

Abstract

The recent increase in online orders in e-commerce leads to logistical challenges such as low hit rates (proportion of successful deliveries). We consider last-mile vehicle routing and scheduling problems in which customer presence probability data are taken into account. The aim is to reduce the expected cost resulting from low hit rates by considering both routing and scheduling decisions simultaneously in the planning phase. We model the problem and solve it by the means of an adaptive large neighborhood search metaheuristic which iterates between the routing and scheduling components of the problem. Computational experiments indicate that using customer-related presence data significantly can yield savings as large as 40% in system-wide costs compared with those of traditional vehicle routing solutions.

Original language	English
Article number	102263
Journal	Transportation Research Part E: Logistics and Transportation Review
Volume	148
Early online date	2 Mar 2021
DOIs	https://doi.org/10.1016/j.tre.2021.102263
Publication status	Published - Apr 2021

Bibliographical note

Funding Information:
This research was partly funded by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189 . This research was also funded by The Dutch Research Council (NWO) Data2Move project under grant 628.009.013 . These supports are greatly acknowledged.

Publisher Copyright:
© 2021 The Author(s)

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Funding

This research was partly funded by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189 . This research was also funded by The Dutch Research Council (NWO) Data2Move project under grant 628.009.013 . These supports are greatly acknowledged.

Keywords

Adaptive large neighborhood search
Customer availability profiles
E-commerce
Last-mile delivery
Vehicle routing

ASJC Scopus subject areas

Business and International Management
Civil and Structural Engineering
Transportation

Access to Document

10.1016/j.tre.2021.102263Licence: CC BY

Cite this

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title = "Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence",

abstract = "The recent increase in online orders in e-commerce leads to logistical challenges such as low hit rates (proportion of successful deliveries). We consider last-mile vehicle routing and scheduling problems in which customer presence probability data are taken into account. The aim is to reduce the expected cost resulting from low hit rates by considering both routing and scheduling decisions simultaneously in the planning phase. We model the problem and solve it by the means of an adaptive large neighborhood search metaheuristic which iterates between the routing and scheduling components of the problem. Computational experiments indicate that using customer-related presence data significantly can yield savings as large as 40% in system-wide costs compared with those of traditional vehicle routing solutions.",

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note = "Funding Information: This research was partly funded by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189 . This research was also funded by The Dutch Research Council (NWO) Data2Move project under grant 628.009.013 . These supports are greatly acknowledged. Publisher Copyright: {\textcopyright} 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

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AU - Woensel, Tom Van

AU - Laporte, Gilbert

N1 - Funding Information: This research was partly funded by the Canadian Natural Sciences and Engineering Research Council under grant 2015-06189 . This research was also funded by The Dutch Research Council (NWO) Data2Move project under grant 628.009.013 . These supports are greatly acknowledged. Publisher Copyright: © 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

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Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence

Abstract

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

Access to Document

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