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doi: 10.1002/net.22022
handle: 11380/1227691 , 11568/1313877 , 11585/896927
AbstractThis article considers a version of the flying sidekick traveling salesman problem in which parcels are delivered to customers by either a truck or a set of identical flying drones. The flights of the drones are limited by the battery endurance and each flight is made of a launch, a service to a customer, and a return: launch and return must happen when the truck is stationary. These operations require time and when multiple drones are launched and/or collected at the same node, their order becomes relevant. The proposed model takes into account the order of these operations as a scheduling problem, because ignoring it could lead to infeasible solutions in the reality due to the possible exceeding of the drones endurance. We propose a set of novel formulations for the problem that can improve the size of the largest instances solved in the literature. We provide a comparison among the formulations, between the multiple drones solutions and the single drone ones, and among different variants of the model.
UAV, aerial drones, formulations, MILP, branch-and-cut, parcel delivery, drone scheduling, Combinatorial optimization, branch-and-cut, formulations, drone scheduling, UAV, aerial drones, UAV; aerial drones; formulations; MILP; branch-and-cut; parcel delivery; drone scheduling, MILP, parcel delivery
UAV, aerial drones, formulations, MILP, branch-and-cut, parcel delivery, drone scheduling, Combinatorial optimization, branch-and-cut, formulations, drone scheduling, UAV, aerial drones, UAV; aerial drones; formulations; MILP; branch-and-cut; parcel delivery; drone scheduling, MILP, parcel delivery
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 39 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
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