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Robust optimization integrating aircraft trajectory and sequence under weather forecast uncertainty

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dc.affiliation.dptoUC3M. Departamento de Bioingenieríaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Ingeniería Aeroespaciales
dc.contributor.authorKamo, Shumpei
dc.contributor.authorRosenow, Judith
dc.contributor.authorFricke, Hartmut
dc.contributor.authorSoler Arnedo, Manuel Fernando
dc.date.accessioned2024-02-12T17:35:07Z
dc.date.available2024-02-12T17:35:07Z
dc.date.issued2023-07-01
dc.description.abstractIntegration of trajectory optimization into sequence optimization is required for next-generation Arrival Managers (AMANs) to support Collaborative Decision-Making (CDM) and implementation of user-preferred 4D trajectories. In addition, considering uncertainty in the optimization is also necessary for making more robust decisions. To achieve these aims, this study proposes a method to integrate the trajectory and sequence of approach aircraft in a single optimization framework and calculate optimal robust solutions against weather forecast uncertainty. This uncertainty is quantified utilizing the ensemble weather forecast and the robust optimizations for trajectory and sequence are formulated in an ensemble approach. To connect the two optimizations, we introduce the so-called performance surfaces, which represent the characteristics of the optimal trajectory. The resulting integrated Trajectory and Sequence (T&S) optimization is a combination of the robust Optimal Control (OC) and Mixed-Integer Nonlinear Programming (MINLP). The MINLP problem is relaxed to the corresponding Nonlinear Programming (NLP) problem to reduce computational costs. In the case study, the trajectory and sequence are simultaneously optimized for two different objectives: the maximum throughput at the merging point and the minimum fuel burn while maintaining the inter-aircraft separation.es
dc.format.extent24es
dc.identifier.bibliographicCitationKamo, S., Rosenow, J., Fricke, H., Soler, M. (2023). Robust optimization integrating aircraft trajectory and sequence under weather forecast uncertainty. In: Transportation Research Part C: Emerging Technologies (152), July. 104187 (24p.) https://doi.org/10.1016/j.trc.2023.104187es
dc.identifier.doihttps://doi.org/10.1016/j.trc.2023.104187
dc.identifier.issn0968-090X
dc.identifier.publicationfirstpage1es
dc.identifier.publicationissueJulyes
dc.identifier.publicationlastpage24es
dc.identifier.publicationtitleTransportation Research Part C: Emerging Technologieses
dc.identifier.publicationvolume152, 104187es
dc.identifier.urihttps://hdl.handle.net/10016/40044
dc.identifier.uxxiAR/0000033709
dc.language.isoenges
dc.publisherElsevieres
dc.rights© 2023 The Authors. Published by Elsevier Ltd.es
dc.rightsThis is an open access article under the CC BY-NC-ND licensees
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaIngeniería Industriales
dc.subject.ecienciaIngeniería Mecánicaes
dc.subject.ecienciaMedio Ambientees
dc.subject.otherAircraft Sequencinges
dc.subject.otherAircraft Trajectory Optimizationes
dc.subject.otherArrival Manager (Aman)es
dc.subject.otherWeather Forecast Uncertaintyes
dc.subject.otherEnsemble Weather Forecastes
dc.subject.otherStochastic Optimizationes
dc.titleRobust optimization integrating aircraft trajectory and sequence under weather forecast uncertaintyes
dc.type.hasVersionVoRes
dspace.entity.typePublication
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