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Cited by 575

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The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones

Open access
Murray, Chase C., Raj, Ritwik·2020·Transportation Research Part C: Emerging Technologies

Abstract

Abstract This paper considers a last-mile delivery system in which a delivery truck operates in coordination with a fleet of unmanned aerial vehicles (UAVs, or drones). Deploying UAVs from the truck enables customers located further from the depot to receive drone-based deliveries. The problem is first formulated as a mixed integer linear program (MILP). However, owing to the computational complexity of this problem, only trivially-sized problems may be solved directly via the MILP. Thus, a heuristic solution approach that consists of solving a sequence of three subproblems is proposed. Extensive numerical testing demonstrates that this approach effectively solves problems of practical size within reasonable runtimes. Additional analysis quantifies the potential time savings associated with employing multiple UAVs. The analysis also reveals that additional UAVs may have diminishing marginal returns. An analysis of five different endurance models demonstrates the effects of these models on UAV assignments. The model and heuristic also support anticipated future systems that feature automation for UAV launch and retrieval.

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Metadata

Authors
Murray, C. C., & Raj, R.
Venue
Transportation Research Part C: Emerging Technologies
Publisher
Elsevier BV
Published
2020-01
Volume
110
Pages
368-398
ISSN
0968-090X (ISSN-L)
OpenAlex
W2915338839
Cited by
575
References
1
FWCI
32.52
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones. https://app.cochat.ai/papers/10.1016/j.trc.2019.11.003
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Murray, C. C., & Raj, R. (2020). The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/j.trc.2019.11.003

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.