Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 276, 2, 2019 DOI: 10.1016/j.ejor.2019.01.039
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Planning efficient 4D trajectories in Air Traffic Flow Management
AU - Dal Sasso, Veronica
AU - Djeumou Fomeni, Franklin
AU - Lulli, Guglielmo
AU - Zografos, Konstantinos G
N1 - This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 276, 2, 2019 DOI: 10.1016/j.ejor.2019.01.039
PY - 2019/7/16
Y1 - 2019/7/16
N2 - In this paper, we focus on designing efficient 4D trajectories for the planning phase of Air Traffic Flow Management (ATFM). A key feature of the proposed approach is the inclusion of stakeholders' preferences and priorities. In particular, we have implemented two priority mechanisms recently developed by Eurocontrol, namely the Fleet Delay Reordering and the Margins.For this purpose, we have customized a multi-objective binary program for the ATFM problem taking into account the specific assumptions required for the ATFM planning phase. To compute the Pareto frontier in a reasonable computational time, we have developed a simulated annealing algorithm. The algorithm has been tested on an instance resembling real world conditions using data extracted from the Eurocontrol data repository. This instance involves four major European airports and their air traffic in one of the busiest days of year 2016, and precisely, October 3rd. The simulated annealing algorithm has shown good computational performances and has provided a good approximation of the Pareto optimal frontier. The results have been validated using Eurocontrol tools and have demonstrated the viability of the proposed approach. Practitioners and stakeholders' representatives have provided positive feedback on the proposed modeling approach and on the inclusion of ATM stakeholders' preferences and priorities.
AB - In this paper, we focus on designing efficient 4D trajectories for the planning phase of Air Traffic Flow Management (ATFM). A key feature of the proposed approach is the inclusion of stakeholders' preferences and priorities. In particular, we have implemented two priority mechanisms recently developed by Eurocontrol, namely the Fleet Delay Reordering and the Margins.For this purpose, we have customized a multi-objective binary program for the ATFM problem taking into account the specific assumptions required for the ATFM planning phase. To compute the Pareto frontier in a reasonable computational time, we have developed a simulated annealing algorithm. The algorithm has been tested on an instance resembling real world conditions using data extracted from the Eurocontrol data repository. This instance involves four major European airports and their air traffic in one of the busiest days of year 2016, and precisely, October 3rd. The simulated annealing algorithm has shown good computational performances and has provided a good approximation of the Pareto optimal frontier. The results have been validated using Eurocontrol tools and have demonstrated the viability of the proposed approach. Practitioners and stakeholders' representatives have provided positive feedback on the proposed modeling approach and on the inclusion of ATM stakeholders' preferences and priorities.
KW - Transportation
KW - Air Traffic Flow Management
KW - 4D trajectories optimization
KW - Multi-objective heuristic
KW - Multi-criteria decision making
U2 - 10.1016/j.ejor.2019.01.039
DO - 10.1016/j.ejor.2019.01.039
M3 - Journal article
VL - 276
SP - 676
EP - 687
JO - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 2
ER -