scholarly journals Simulation optimization of air traffic delay cost

2002 ◽  
Author(s):  
N.L. Kleinman ◽  
S.D. Hill ◽  
V.A. Ilenda
Keyword(s):  
Simulation Optimization ◽  
Air Traffic ◽  
Delay Cost ◽  
Traffic Delay

scholarly journals Central Authority–Controlled Air Traffic Flow Management: An Optimization Approach

2021 ◽  
Author(s):  
Sadeque Hamdan ◽  
Ali Cheaitou ◽  
Oualid Jouini ◽  
Tobias Andersson Granberg ◽  
Zied Jemai ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Air Traffic ◽  
Total System ◽  
Central Authority ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Network Cost ◽  
Air Traffic Flow ◽  
Traffic Flow Management ◽  
Delay Cost

Despite various planning efforts, airspace capacity can sometimes be exceeded, typically because of disruptive events. Air traffic flow management (ATFM) is the process of managing flights in this situation. In this paper, we present an ATFM model that accounts for different rerouting options (path rerouting and diversion) and preexisting en route flights. The model proposes having a central authority to control all decisions, which is then compared with current practice. We also consider interflight and interairline fairness measures in the network. We use an exact approach to solve small- to medium-sized instances, and we propose a modified fix-and-relax heuristic to solve large-sized instances. Allowing a central authority to control all decisions increases network efficiency compared with the case where the ATFM authority and airlines control decisions independently. Our experiments show that including different rerouting options in ATFM can help reduce delays by up to 8% and cancellations by up to 23%. Moreover, ground delay cost has much more impact on network decisions than air delay cost, and network decisions are insensitive to changes in diversion cost. Furthermore, the analysis of the tradeoff between total network cost and overtaking cost shows that adding costs for overtaking can significantly improve fairness at only a small increase in total system cost. A balanced total cost per flight among airlines can be achieved at a small increase in the network cost (0.2%–3.0%) when imposing airline fairness. In conclusion, the comprehensiveness of the model makes it useful for analyzing a wide range of alternatives for efficient ATFM.

scholarly journals Signal Processing and Machine Learning for Air Traffic Delay Prediction

2021 ◽  
Vol 58 ◽  
pp. 463-470
Author(s):  
Víctor M. Tenorio ◽  
Antonio G. Marques ◽  
Luis Cadarso
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Air Traffic ◽  
Traffic Delay ◽  
Delay Prediction

Traffic Delay Cost Savings Associated with Trenchless Technology

1999 ◽  
Vol 5 (2) ◽  
pp. 45-51 ◽  
Author(s):  
Susan Tighe ◽  
Thomas Lee ◽  
Robert McKim ◽  
Ralph Haas
Keyword(s):  
Cost Savings ◽  
Trenchless Technology ◽  
Delay Cost ◽  
Traffic Delay

Stochastic Simulation Optimization for Route Selection Strategy Based on Flight Delay Cost

2018 ◽  
Vol 35 (06) ◽  
pp. 1850045
Author(s):  
Yong Tian ◽  
Bojia Ye ◽  
Marc Sáez Estupiñá ◽  
Lili Wan
Keyword(s):  
Stochastic Simulation ◽  
Simulation Optimization ◽  
Optimization Technique ◽  
Civil Aviation ◽  
Selection Strategy ◽  
Route Selection ◽  
Full Information ◽  
Adverse Weather ◽  
Delay Cost ◽  
Flight Delay

The continuous and strong growth of the civil aviation in the world combined with the severe adverse weather problem have made necessary the collaboration between the different civil aviation agents to improve the management of the capacity-demand imbalances in the airspace. In this paper, we consider a stochastic simulation optimization problem for air route selection strategy based on flight delay cost. The problem takes consideration of airspace capacity and demand uncertainty, three strategies, including collaborative reroute strategy (CRS), full information reroute strategy (FIRS) and hybrid stated route preference strategy (HSR), are employed to mitigate the flight delay cost. To find the best strategy, a discrete event simulation model is built by Arena Software, and the Monte Carlo method combined with the OCBA simulation optimization technique is employed for assessing a common severe convective weather scenario in the Central and Southern China airspace. Simulation results imply that HSR schemes show better system-wide performance than CRS and FIRS, these benefits are supposed to come from the batch allocations method. Although the airline can receive full information in advance, FIRS does not show obvious advantage in reducing the total airborne waiting time than CRS. For the system-wide performance FIRS is better than CRS, but not as good as HSR.

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