Dynamic Arrival Scheduling Based on Branch and Bound Algorithm

Wang, Fei; Zhang, Junfeng; Chen, Qiang; Sui, Dong

doi:10.1061/9780784479292.006

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…In terms of solution algorithms, Bae and Clarke 6 introduced the delay saturation weighting factor and proposed an improved mixed integer planning algorithm. In addition, the scatter search algorithm, 7 branch and bound method, 8 genetic algorithm (GA), 4.9,10,11 greedy algorithm, 12 and simulated annealing algorithm 13 have been used to solve the approach scheduling problem. Most scholars use traditional optimization algorithms, but developing a more effective and accurate solution algorithm in addition to the commonly used traditional algorithms is an urgent problem; for example, the swarm intelligence algorithm has a strong global search ability and high convergence speed, so the introduction of swarm intelligence algorithms into the study of the flight scheduling problem may be a helpful tactic.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimization of terminal area arrival flight sorting based on an improved sparrow search algorithm

Zhao,

Liang

2024

Science Progress

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At present, airspace congestion and flight delays have become widespread concerns. This study aims to optimize the sequencing of arrival flights in the terminal area of multirunway airports. Considering the constraints of multiple runways, slant intervals and moving flight positions, this article establishes an optimization model for arrival flight sequencing in a multirunway airport terminal area. Accordingly, an improved sparrow search algorithm (ISSA) is proposed based on Chebyshev chaotic mapping, the golden sine strategy, and the variable neighborhood strategy. Through six basic test functions, the ISSA is compared with particle swarm optimization, the whale optimization algorithm, the genetic algorithm, and other algorithms to verify its superiority. Finally, two sets of instance data from Kunming Changshui Airport were used for experiments. The results show that the total delay times (TDTs) of small-scale flights (number of aircraft: 29) and large-scale flights (number of aircraft: 147) are 55.3% and 20.5% lower, respectively, than those of the first-come-first-served algorithm. The superiority of the ISSA designed in this article is verified, and it can significantly reduce the TDTs of arrival flights. It is suitable for optimizing arrival flights during peak hours at most airports. This approach provides theoretical support for optimizing the sorting of flights in terminal areas.

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