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hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorFurini, Fabio
hal.structure.identifier
dc.contributor.authorPersiani, Carlo Alfredo
hal.structure.identifierD.E.I. - University of Bologna.
dc.contributor.authorToth, Paolo
dc.date.accessioned2017-03-17T16:35:43Z
dc.date.available2017-03-17T16:35:43Z
dc.date.issued2016
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16382
dc.language.isoenen
dc.subjectInteger programmingen
dc.subjectTime dependent TSPen
dc.subjectDronesen
dc.subjectAir traffic managementen
dc.subject.ddc519en
dc.subject.classificationjelC61en
dc.titleThe Time Dependent Traveling Salesman Planning Problem in Controlled Airspaceen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenThe integration of drones into civil airspace is one of the most challenging problems for the automation of the controlled airspace, and the optimization of the drone route is a key step for this process. In this paper, we optimize the route planning of a drone mission that consists of departing from an airport, flying over a set of mission way points and coming back to the initial airport. We assume that during the mission a set of piloted aircraft flies in the same airspace and thus the cost of the drone route depends on the air traffic and on the avoidance maneuvers used to prevent possible conflicts. Two air traffic management techniques, i.e., routing and holding, are modeled in order to maintain a minimum separation between the drone and the piloted aircraft. The considered problem, called the Time Dependent Traveling Salesman Planning Problem in Controlled Airspace (TDTSPPCA), relates to the drone route planning phase and aims to minimize the total operational cost. Two heuristic algorithms are proposed for the solution of the problem. A mathematical formulation based on a particular version of the Time Dependent Traveling Salesman Problem, which allows holdings at mission way points, and a Branch and Cut algorithm are proposed for solving the TDTSPPCA to optimality. An additional formulation, based on a Travelling Salesman Problem variant that uses specific penalties to model the holding times, is proposed and a Cutting Plane algorithm is designed. Finally, computational experiments on real-world air traffic data from Milano Linate Terminal Maneuvering Area are reported to evaluate the performance of the proposed formulations and of the heuristic algorithms.en
dc.relation.isversionofjnlnameTransportation Research Part B: Methodological
dc.relation.isversionofjnlvol90en
dc.relation.isversionofjnldate2016-08
dc.relation.isversionofjnlpages38-55en
dc.relation.isversionofdoi10.1016/j.trb.2016.04.009en
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2017-03-17T16:27:05Z
hal.identifierhal-01492016*
hal.version1*
hal.author.functionaut
hal.author.functionaut
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