On the min-cost Traveling Salesman Problem with Drone

The efficiency and dynamism of unmanned aerial vehicles, or drones, have presented substantial application opportunities in several industries in the last years. Notably, logistic companies have given close attention to these vehicles to reduce delivery time and operational cost. A variant of the traveling salesman problem (TSP), called the flying sidekick traveling salesman problem, was introduced involving drone‐assisted parcel delivery. The drone launches from the truck, proceeds to deliver parcels to a customer, and then is recovered by the truck at a third location. While the drone travels through a trip, the truck delivers parcels to other customers as long as the drone has enough battery to hover waiting for the truck. This work proposes a hybrid heuristic where the initial solution is created from the optimal TSP solution reached by a TSP solver. Next, an implementation of the general variable neighborhood search is employed to obtain the delivery routes of truck and drone. Computational experiments show the potential of the algorithm to improve significantly delivery time. Furthermore, we provide a new set of instances based on the well‐known traveling salesman problem library instances.

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“…Different acronyms may correspond to the same problem, as can be seen in Ha et al. () and Ferrandez et al. ().…”

Section: Related Workmentioning

confidence: 93%

“…Ha et al. () describe a variant of the FSTSP. They propose an MILP formulation and two methods to solve the problem, a heuristic based on Greedy Randomized Adaptive Search Procedure (GRASP) and TSP‐LS (Traveling Salesman Problem ‐ Local Search).…”

Section: Related Workmentioning

confidence: 99%

A variable neighborhood search for flying sidekick traveling salesman problem

Freitas

Penna

2019

Int Trans Operational Res

161

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“…One broad categorization of related problems involves surveillance applications with cooperative air and ground assets [5,23]. There are also certain kinds of cooperative routing problems for GV and UAV, called TSP with drone (TSP-D) [24,25,26,27] and VRP with drone (VRP-D) [28,29]. In these problems, the UAV is carried by a mobile platform that keeps on moving on its own route while UAV executes its mission.…”

Section: Literature Reviewmentioning

confidence: 99%

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle

Luo

Liu

Shi

2017

Sensors

133

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In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0–1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25–200 targets, 12–80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable.

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“…In addition, we establish bounds which relate the VRPD to two other well‐established problems, which hint at future corresponding computational methods. In parallel with our somewhat theoretical approach, other researchers (e.g., see ) propose computational approaches to address special cases of the VRPD.…”

Section: Introductionmentioning

confidence: 99%

The vehicle routing problem with drones: Extended models and connections

2017

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The vehicle routing problem with drones (VRPD) is inspired by the increasing interest in commercial drone delivery by companies such as Amazon, Google, DHL, and Walmart. In our model, a fleet of m homogeneous trucks each carries k drones with a speed of α times that of the truck. Each drone may dispatch from the top of the truck and carry a package to a customer location. The drone then returns to the top of its truck to recharge or swap batteries (we assume instantaneously). The truck itself is allowed to move and deliver packages, but must be stationary at a delivery location or the depot when launching or retrieving drones. The goal is to minimize the completion time to deliver all packages and return all vehicles back to the central depot. In this article, we review and extend several worst‐case results from an earlier paper and we make connections with another practical variant of the vehicle routing problem and with Amdahl's Law. We find that the VRPD model offers some important practical advantages. The drones allow the truck to parallelize tasks and they are able to take advantage of crow‐fly distances. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 70(1), 34–43 2017

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On the min-cost Traveling Salesman Problem with Drone

Cited by 456 publications

References 17 publications

A variable neighborhood search for flying sidekick traveling salesman problem

A variable neighborhood search for flying sidekick traveling salesman problem

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle

The vehicle routing problem with drones: Extended models and connections

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