Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Otto, Alena; Agatz, Niels; Campbell, James F.; Golden, Bruce L.; Pesch, Erwin

doi:10.1002/net.21818

Cited by 657 publications

(345 citation statements)

References 296 publications

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“…It is the first to explore the addition of drones to vehicle fleets for the SDD, a business model being considered by companies such as Amazon. Second, this paper is the first to present a delivery scheme for drone delivery operations, answering the call in Otto et al that says that “… future research should work out dynamic planning schemes for a range of relevant drone operations.” Third, we present a comprehensive Markov decision process model for a complex dynamic vehicle routing problem. Fourth, for a large set of generated and real‐world instance settings, our PFA increases the number of same‐day services significantly compared to other PFA benchmark policies.…”

Section: Introductionmentioning

confidence: 78%

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Same‐day delivery with heterogeneous fleets of drones and vehicles

2018

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In this paper, we analyze how drones can be combined with regular delivery vehicles to improve same‐day delivery performance. To this end, we present a dynamic vehicle routing problem with heterogeneous fleets. Customers order goods over the course of the day. These goods are delivered either by a drone or by a regular transportation vehicle within a delivery deadline. Drones are faster, but have a limited capacity as well as require charging after use. In the same‐day context, vehicle capacity is not a constraint, but vehicles are slow due to urban traffic. To decide whether an order is delivered by a drone or by a vehicle, we present a policy function approximation based on geographical districting. Our computational study reveals two major implications. First, geographical districting is highly effective increasing the expected number of same‐day deliveries. Second, a combination of drone and vehicle fleets may significantly reduce the required delivery resources.

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Section: Introductionmentioning

confidence: 78%

“…In this section of the literature review, we focus on work combining conventional vehicles with drones for delivery. For a recent survey on drone routing, the interested reader is referred to Otto et al . None of the papers cited in Otto et al or subsequently in this paper include the stochasticity and dynamism of the SDDPHF.…”

Section: Literature Reviewmentioning

confidence: 99%

Same‐day delivery with heterogeneous fleets of drones and vehicles

2018

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“…In the recent survey [21], the authors treat deeply the problems that arise when drones are coupled with trucks for deliveries in the commercial sector: we head the interested reader to that survey. The survey classifies the PDSTSP in the class Drones and vehicles performing independent tasks, under the wider class called Planning combined operations of drones with other vehicles.…”

Section: Literature Reviewmentioning

confidence: 99%

Matheuristic algorithms for the parallel drone scheduling traveling salesman problem

2020

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In a near future drones are likely to become a viable way of distributing parcels in a urban environment. In this paper we consider the parallel drone scheduling traveling salesman problem, where a set of customers requiring a delivery is split between a truck and a fleet of drones, with the aim of minimizing the total time required to service all the customers.We present a set of matheuristic methods for the problem. The new approaches are validated via an experimental campaign on two sets of benchmarks available in the literature. It is shown that the approaches we propose perform very well on small/medium size instances. Solving a mixed integer linear programming model to optimality leads to the first optimality proof for all the instances with 20 customers considered, while the heuristics are shown to be fast and effective on the same dataset. When considering larger instances with 48 to 229 customers, the results are competitive with stateof-the-art methods and lead to 28 new best known solutions out of the 90 instances considered.

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“…On the other hand, drone use for inspection sensing and surveillance along linear features can be seen as extensions of well‐studied ARPs (i.e., the Chinese postman problem [CPP] and the rural postman problem [RPP]). Otto et al review academic research on optimization approaches for a variety of routing problems for the commercial use of drones.…”

Section: Introductionmentioning

confidence: 99%

Drone arc routing problems

et al. 2018

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In this article, we present some drone arc routing problems (Drone ARPs) and study their relation with well‐known postman ARPs. Applications for Drone ARPs include traffic monitoring by flying over roadways, infrastructure inspection such as by flying along power transmission lines, pipelines or fences, and surveillance along linear features such as coastlines or territorial borders. Unlike the postmen in traditional ARPs, drones can travel directly between any two points in the plane without following the edges of the network. As a consequence, a drone route may service only part of an edge, with multiple routes being used to cover the entire edge. Thus the Drone ARPs are continuous optimization problems with an infinite number of feasible solutions. In order to solve them as a discrete optimization problem, we approximate each curve in the plane by a polygonal chain, thus allowing the vehicle to enter and leave each curve only at the points of the polygonal chain. If the capacity of the vehicles is unlimited, the resulting problem is a rural postman problem (RPP). We propose an algorithm that iteratively solves RPP instances with an increasing number of points of the polygonal chain and present results on several sets of instances. We also briefly discuss the case in which the drones have limited capacity and several drones are needed.

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Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Cited by 657 publications

References 296 publications

Same‐day delivery with heterogeneous fleets of drones and vehicles

Same‐day delivery with heterogeneous fleets of drones and vehicles

Matheuristic algorithms for the parallel drone scheduling traveling salesman problem

Drone arc routing problems

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