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research article

A survey on vehicle–drone cooperative delivery operations optimization: Models, methods, and future research directions

Zhou, Jing
•
Yi, Jin
•
Yang, Zhenyu  
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February 1, 2025
Swarm and Evolutionary Computation

With the rise of technology and market demand, unmanned devices, particularly drones, are increasingly used in logistics due to their speed and cost-efficiency. However, the persistence of limiting factors such as battery life and payload capacity has rendered vehicle-drone cooperative delivery an emerging and promising research area. This paper compiles relevant literature on the cooperative operation of vehicles and drones, summarizing key research directions, which encompass a novel classification framework, commonly utilized mathematical models, and solutions. Additionally, we collected algorithmic test cases employed in current research. Finally, the paper analyzes the current research status and the existing challenges and provides suggestions for future research directions.

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Type
research article
DOI
10.1016/j.swevo.2024.101780
Scopus ID

2-s2.0-85210021077

Author(s)
Zhou, Jing

Chongqing University

Yi, Jin

Chongqing University

Yang, Zhenyu  

École Polytechnique Fédérale de Lausanne

Pu, Huayan

Chongqing University

Li, Xinyu

Huazhong University of Science and Technology

Luo, Jun

Chongqing University

Gao, Liang

Huazhong University of Science and Technology

Date Issued

2025-02-01

Published in
Swarm and Evolutionary Computation
Volume

92

Article Number

101780

Subjects

Combinatorial optimization

•

Literature review

•

Vehicle–drone cooperative delivery

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LUTS  
FunderFunding(s)Grant NumberGrant URL

Independent Research Project-Key Program

State Key Laboratory of Mechanical Transmission for Advanced Equipment, China

Entrepreneurship and Innovation Support Plan of Chongqing for Returned Overseas Scholars, China

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Available on Infoscience
January 25, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/244209
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