Optimization for drone and drone-truck combined operations: A review of the state of the art and future directions
By S. Chung, Bhawesh Sah, Jason Lee. Computers & Operations Research, 2020
362 citations recorded by the source corpus.
Abstract This paper surveys the state-of-the-art optimization approaches in the civil application of drone operations (DO) and drone-truck combined operations (DTCO) including construction/infrastructure, agriculture, transportation/logistics, security/disaster management, entertainment/media, etc. In particular, this paper reviews ongoing research on various optimization issues related to DO and DTCO including mathematical models, solution methods, synchronization between a drone and a truck, and barriers in implementing DO and DTCO. First, the paper introduces DO and DTCO and their applications, and explores some previous works including survey papers. In addition, this paper surveys the state of the art of DO and DTCO studies and discusses the research gaps in the literature. Furthermore, the detailed review of DTCO models and solution methods are reviewed. Finally, future research directions are discussed.
Subfields: Aerospace Engineering, Building and Construction, Industrial and Manufacturing Engineering
View Paper: https://www.semanticscholar.org/paper/8fda94a6532996084b59a6090fd04ccbad0db1f2
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Citations in the corpus
- Applications and Research avenues for drone-based models in logistics: A classification and review (2021, background): “…are a number of structured literature reviews on drone logistics (see, e.g., Otto et al., 2018; Khoufi et al., 2019; Rojas Viloria et al., 2020; Chung et al., 2020; Macrina et al., 2020), none of these existing contributions provides a systematic and scalable classification framework that…”