scholarly journals Effect of Uncertainty on Deterministic Runway Scheduling

2011 ◽  
Author(s):  
Gautam Gupta ◽  
Waqar Malik ◽  
Yoon Jung
Keyword(s):  
Runway Scheduling

Runway scheduling during winter operations

Omega ◽  
2020 ◽  
pp. 102325
Author(s):  
Maximilian Pohl ◽  
Rainer Kolisch ◽  
Maximilian Schiffer
Keyword(s):  
Runway Scheduling

scholarly journals Time-Indexed Formulations for the Runway Scheduling Problem

2017 ◽  
Vol 51 (4) ◽  
pp. 1196-1209 ◽  
Author(s):  
Pasquale Avella ◽  
Maurizio Boccia ◽  
Carlo Mannino ◽  
Igor Vasilyev
Keyword(s):  
Scheduling Problem ◽  
Runway Scheduling

Airport runway scheduling

4OR ◽  
2011 ◽  
Vol 9 (2) ◽  
pp. 115-138 ◽  
Author(s):  
Julia A. Bennell ◽  
Mohammad Mesgarpour ◽  
Chris N. Potts
Keyword(s):  
Airport Runway ◽  
Runway Scheduling

Hybrid Metaheuristics to Aid Runway Scheduling at London Heathrow Airport

2007 ◽  
Vol 41 (1) ◽  
pp. 90-106 ◽  
Author(s):  
Jason A. D. Atkin ◽  
Edmund K. Burke ◽  
John S. Greenwood ◽  
Dale Reeson
Keyword(s):  
Hybrid Metaheuristics ◽  
Runway Scheduling

scholarly journals Tactical Runway Scheduling for Demand and Delay Management

2021 ◽  
Vol 1024 (1) ◽  
pp. 012108
Author(s):  
Álvaro Rodríguez-Sanz ◽  
Pablo López Cózar ◽  
Javier A. Pérez-Castán ◽  
Fernando Gómez Comendador
Keyword(s):  
Delay Management ◽  
Runway Scheduling

scholarly journals Taxiing Route Scheduling between Taxiway and Runway in Hub Airport

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Yu Jiang ◽  
Xinxing Xu ◽  
Honghai Zhang ◽  
Yuxiao Luo
Keyword(s):  
Genetic Algorithm ◽  
Delay Time ◽  
Optimization Method ◽  
Improved Genetic Algorithm ◽  
Route Length ◽  
Optimizing Model ◽  
The Right ◽  
Hub Airport ◽  
Runway Scheduling ◽  
Route Scheduling

To guarantee the operation safety of airport, improve the efficiency of surface operation, and enhance the fairness of taxiing route scheduling, an optimizing model is established for the airport surface taxiing route scheduling. Reducing the total aircraft taxiing route length and reducing the waiting delay time are the goals of the model by controlling the initial taxiing time of aircraft and choosing the right taxiing route. The model can guarantee the continuous taxiing for all aircraft without conflicts. The runway scheduling is taken into consideration in the model to optimize the surface operation. The improved genetic algorithm is designed for simulation and validation. The simulation results show that compared with the ant colony optimization method, the improved genetic algorithm reduces the total extra taxiing distance by 47.8% and the total waiting delay time decreases by 21.5%. The optimization model and improved genetic algorithm are feasible. The optimization of taxiing route method can provide decision support for hub airports.

Optimal mixed-mode runway scheduling — Mixed-integer programming for ATC scheduling

2011 ◽  
Author(s):  
Hartmut Helmke ◽  
Olga Gluchshenko ◽  
Alexander Martin ◽  
Andrea Peter ◽  
Sebastian Pokutta ◽  
...  
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Mixed Mode ◽  
Mixed Integer ◽  
Runway Scheduling

A branch and cut heuristic for a runway scheduling problem

2016 ◽  
Vol 77 (11) ◽  
pp. 1985-1993 ◽  
Author(s):  
I. L. Vasilyev ◽  
P. Avella ◽  
M. Boccia
Keyword(s):  
Branch And Cut ◽  
Scheduling Problem ◽  
Runway Scheduling
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