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|Title:||A study of optimization of air traffic network and flight schedules||Authors:||Sailauov, Tolebi||Keywords:||DRNTU::Engineering::Aeronautical engineering::Aviation||Issue Date:||2019||Source:||Sailauov, T. (2019). A study of optimization of air traffic network and flight schedules. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||South-East Asia is considered one of the fastest air traffic growing regions in the world. Congested air traffic and weather conditions have thus become major factors in air traffic management. Models have been proposed to manage air traffic flow efficiently and to solve congested airspace problems. In order to manage air traffic flow efficiently, this thesis focused on forecasting air traffic, rescheduling of flights and restructuring an air network. In this research the model for air traffic forecasting was able to forecast the country, city-pair and airport-pair air traffic. Results show that the passenger forecasting for Singapore has dependence not only on that country but on neighbouring countries as well. The research predicts that the passenger movements in Changi airport will increase up to 81.65 million people by year 2023, which is 31.23 % more than that in 2017. Also, the number of passenger aircraft between Singapore and Jakarta city-pair will increase up to 34702 by year 2023, which is 26.6 % more than that in 2017. In addition, the number of passenger aircraft between Changi airport and KLIA airport-pair will be between 31698 and 40311 by year 2023. The model to reschedule flights focuses on solving reduced capacity problems and on reducing delays efficiently. Rescheduling of flights was done operationalizing and satisfying the constraints of delay costs, airport departure and arrival capacities, waypoints’ capacities, routes capacity and rerouting options. Results show that in the flights between KLIA and Changi airport, ground delays were reduced by 4.98 min and 3.05 min on average. More importantly, the airborne delays were reduced by 2.70 min and 3.95 min on average. The model made sure none of the flights got delayed longer than a specific time and ensured fairness to all flights. Also, a model was developed to reconstruct the air network. A case study was implemented involving 8 airports. The total route distance and the objective function were reduced by 1.53% and 1.48 % respectively. The results show that restructuring the air network can reduce flights’ distances using proper merging methods.||URI:||https://hdl.handle.net/10356/104791
|DOI:||10.32657/10220/48614||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||MAE Theses|
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Updated on Jan 29, 2023
Updated on Jan 29, 2023
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