• Advances in aircraft and spacecraft science
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• v.9 no.4
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• pp.335-347
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• 2022

Airport operations are well-known as a bottleneck in the air traffic system, putting growing pressure on the world's busiest airports to schedule arrivals and departures as efficiently as possible. Effective planning and control are essential for increasing airport efficiency and reducing aircraft delays. Many algorithms for controlling the arrival/departure queuing area are handled, considering it as first in first out queues, where any available aircraft can take off regardless of its relative sequence with other aircraft. In the suggested system, this problem was compared to the problem of scheduling n tasks (plane takeoffs and landings) on a multiple machine (runways). The proposed technique decreases delays (via efficient runway allocation or allowing aircraft to be expedited to reach a scheduled time) to enhance runway capacity and decrease delays. The aircraft scheduling problem entails arranging aircraft on available runways and scheduling their landings and departures while considering any operational constraints. The topic of this work is the scheduling of aircraft landings and takeoffs on multiple runways. Each aircraft's takeoff and landing schedules have time windows, as well as minimum separation intervals between landings and takeoffs. We present and evaluate a variety of comprehensive concepts and solutions for scheduling aircraft arrival and departure times, intending to reduce delays relative to scheduled times. When compared to First Come First Serve scheduling algorithm, the suggested strategy is usually successful in reducing the average waiting time and average tardiness while optimizing runway use.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.3
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• pp.48-54
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• 2016

This paper proposes a prediction model of air traffic controller's take-off clearance under mixed mode runway operations. The proposed model has its purpose on the better prediction of the air traffic controller's clearance on take-offs of departure aircraft by considering various factors. For this purpose, support vector machine classification algorithm is used for the proposed model. The proposed model is applied to real air traffic operations to demonstrate its performances.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.161-168
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• 2014

The optimal solution of minimum cost for aircraft landing problem(ALP) is very difficult problem because the approached aircraft are random time interval. Therefore this problem has been applied by various meta heuristic methods. This paper suggests O(nlog n) polynomial time heuristic algorithm to obtain the optimal solution for ALP. This algorithm sorts the target time of aircraft into ascending order. Then we apply the optimization of change the landing sequence take account of separation time and the cost of landing. For the Airland1 through Airland8 of benchmark data of ALP, we choose 25 data until the number of runway m that the total landing cost is 0. We can be obtain the optimal solution for all of the 25 data. Especially we can be improve the known optimal solution for m = 1of Airland8.