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  4. Constraint reconciliation optimization to minimize primary and reactionary delay in a research network strategic tool
 
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Constraint reconciliation optimization to minimize primary and reactionary delay in a research network strategic tool

Citation Link: https://doi.org/10.15480/882.13358
Publikationstyp
Journal Article
Date Issued
2024-04-25
Sprache
English
Author(s)
Berling, Jan 
Lufttransportsysteme M-28  
Lau, Alexander  
Lufttransportsysteme M-28  
Gollnick, Volker  
Lufttransportsysteme M-28  
TORE-DOI
10.15480/882.13358
TORE-URI
https://hdl.handle.net/11420/49357
Journal
CEAS Aeronautical Journal  
Volume
15
Issue
4
Start Page
1015
End Page
1030
Citation
CEAS Aeronautical Journal 15 (4): 1015-1030 (2024)
Publisher DOI
10.1007/s13272-023-00708-4
Scopus ID
2-s2.0-85191238688
Publisher
Springer
When regulated network capacities are violated, flights may be delayed to meet time-based slot restrictions. In addition, reactionary delays occur when time buffers to subsequent flight legs are exceeded. This work aims to minimize both—primary and reactionary delays in a dynamic simulation of the European Air Transportation System. The slot allocation process is solved by minimizing network delay with a binary optimization approach instead of using the current first-planned–first-served principle. The new module presented in this study, called constraint reconciliation and optimization (CRO), is applied within EUROCONTROL’s Research Network Strategic Tool (R-NEST). The results are compared to delays generated by R-NEST’s computer-aided slot allocation (ISA–CASA). In simulations of tactical air traffic flow management (ATFM) operations, time is iterated over the day and flight plans are updated with random and propagated delays. The computational complexity of all possible delay- and slot-entry-permutations is reduced by the method of column generation for solving large linear problems. Three validation scenarios that contain flight plans, rotation margins, sector configurations, regulations, and deterministic or stochastic delays are evaluated. In the most realistic scenario, compared to ISA–CASA, CRO reduces primary and reactionary delays by up to 16% while achieving low levels of airspace sector and airport overloads and fast computation times.
Subjects
Air Traffic Flow Management
Demand Capacity Balancing
European Air Transportation System
Fairness
Optimization
Reactionary Delay
DDC Class
629.1: Aviation
Funding(s)
Projekt DEAL  
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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