scholarly journals SPSA/SIMMOD optimization of air traffic delay cost

1997 ◽  
Author(s):  
N.L. Kleinman ◽  
S.D. Hill ◽  
V.A. Ilenda
Keyword(s):  
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

scholarly journals Clusters and communities in air traffic delay networks

2016 ◽  
Author(s):  
Karthik Gopalakrishnan ◽  
Hamsa Balakrishnan ◽  
Richard Jordan
Keyword(s):  
Air Traffic ◽  
Traffic Delay

scholarly journals Data-Driven Modeling of Systemic Air Traffic Delay Propagation: An Epidemic Model Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Shanmei Li ◽  
Dongfan Xie ◽  
Xie Zhang ◽  
Zhaoyue Zhang ◽  
Wei Bai
Keyword(s):  
Epidemic Model ◽  
Air Traffic ◽  
System Level ◽  
Fluctuation Analysis ◽  
Probabilistic Prediction ◽  
Complex Network Theory ◽  
Delay Propagation ◽  
Traffic Delay ◽  
Flight Delay

To better understand the mechanism of air traffic delay propagation at the system level, an efficient modeling approach based on the epidemic model for delay propagation in airport networks is developed. The normal release rate (NRR) and average flight delay (AFD) are considered to measure airport delay. Through fluctuation analysis of the average flight delay based on complex network theory, we find that the long-term dynamic of airport delay is dominated by the propagation factor (PF), which reveals that the long-term dynamic of airport delay should be studied from the perspective of propagation. An integrated airport-based Susceptible-Infected-Recovered-Susceptible (ASIRS) epidemic model for air traffic delay propagation is developed from the network-level perspective, to create a simulator for reproducing the delay propagation in airport networks. The evolution of airport delay propagation is obtained by analyzing the phase trajectory of the model. The simulator is run using the empirical data of China. The simulation results show that the model can reproduce the evolution of the delay propagation in the long term and its accuracy for predicting the number of delayed airports in the short term is much higher than the probabilistic prediction method. The model can thus help managers as a tool to effectively predict the temporal and spatial evolution of air traffic delay.

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