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Drone location and vehicle fleet planning with trucks and aerial drones

Titelangaben

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Rave, Alexander ; Fontaine, Pirmin ; Kuhn, Heinrich:
Drone location and vehicle fleet planning with trucks and aerial drones.
In: European Journal of Operational Research. 308 (2023) 1. - S. 113-130.
ISSN 0377-2217

Volltext

Volltext Link zum Volltext (externe URL):
https://doi.org/10.1016/j.ejor.2022.10.015

Kurzfassung/Abstract

In the context of parcel delivery, aerial drones have great potential that particularly applies in rural areas. In these areas drones mostly operate faster than trucks. As drones are limited in their payload, a combination of trucks and drones can be beneficial in reducing last-mile delivery costs. There are two different delivery methods that combine truck and drone delivery: trucks and drones collaborating with each other with drones launched from trucks, and trucks and drones serving customers independently of each other with drones launched from microdepots or the central distribution center.

We develop a tactical planning model that decides on the cost-optimal vehicle fleet and the location of dedicated drone stations of a logistics service provider that minimizes total costs. The problem setting is modeled as a mixed-integer linear program that allows the assessment of benefits of different transport concepts as well as the impact of mixing different delivery modes. To solve larger instances we develop a specialized adaptive large neighborhood search.

We present a numerical study for parcel delivery in a rural area where customers live in scattered settlements, e.g., villages or hamlets. The case study shows that it is best to launch drones both from trucks and dedicated drone stations in 58% of all scenarios considered. This fleet mix leads to average cost savings of 33,3 %
compared to an only truck scenario and 14,1 % if trucks and drones launched from trucks are considered for delivery. Moreover, we find 17 new best-known solutions for benchmark instances from the literature.

Weitere Angaben

Publikationsform:Artikel
Sprache des Eintrags:Englisch
Institutionen der Universität:Wirtschaftswissenschaftliche Fakultät > Betriebswirtschaftslehre > Lehrstuhl für Operations Management
DOI / URN / ID:10.1016/j.ejor.2022.10.015
Open Access: Freie Zugänglichkeit des Volltexts?:Nein
Peer-Review-Journal:Ja
Verlag:Elsevier
Die Zeitschrift ist nachgewiesen in:
Titel an der KU entstanden:Ja
KU.edoc-ID:31603
Eingestellt am: 10. Feb 2023 11:50
Letzte Änderung: 06. Mai 2024 09:14
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/31603/
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