臺灣博碩士論文加值系統

隨著航班數量的增加，各個機場可能會出現擁堵情況。因此儘可能有效地安排飛機滑行路徑的是減少空側擁堵的解決方案。 本研究旨在優化台灣最繁忙的機場-桃園國際機場 (TPE) 飛機的滑行路線。應用基因遺傳算法為飛機滑行尋找最佳路徑是。首先基因遺傳算法初始設定人口是根據可用的滑行道而產生。然後通過50%的染色體互換交叉和1%的突變率計算產生出滑行路徑。優化選擇是根據最短的滑行時間，此外以沒有衝突點被用作前提制約條件，重複計算直到 100 次疊代。 結果表明在桃機可能的滑行路線有限的情況下，遺傳算法可以優化和減少總滑行時間 1.8%。 這項研究也將延誤、取消、地面車輛移動、推遲時間和封閉的滑行道路線等因素列入考量。

With the increasing number of flights, congestion may happen at various airports. Therefore, arranging the taxi process at a taxiway as effective as possible is one of the main solutions to reduce taxiway congestion. This study aims to optimize the taxiway routes at Taoyuan International Airport (IATA code TPE). The Genetic Algorithm is applied to find the best route for the taxi process at TPE airport which is the busiest airport in Taiwan. First, the initial population is produced based on the availiable taxiways. Then, the reproduction is generated by crossover of 50% and mutation rate of 1 %. The selection is conducted based on the shortest taxi time. In addition, no conflict point is used as a constraint. The calculation is repeated until 100 iterations. The result shows that Genetic Algorithm can optimize and reduce total taxi time by 1.8% due to limited possible taxi route. This study also considers some delays or cancellations, ground vehicle movements, push back time, and closed taxiway routes.

摘要......i
Abstract......ii
Table of Contents......iv
List of Tables......vi
List of Figures......vii
Symbols......ix
Chapter 1: Introduction......1
1.1 Background......1
1.2 Research Purpose......1
1.3 Problem Description......2
1.4 Research Questions......2
1.5 Thesis Outlines......2
Chapter 2: Literature Review......5
2.1 Classification from Optimization technique......5
2.2 Evolutionary Algorithm Principle......7
2.3 Taxiway......8
2.3.1 Width from Taxiway......8
2.3.2 Clereance from Taxiwayside......10
2.3.3 Taxiway Curves......10
2.3.4 Taxiway Sight Distance......10
2.3.5 Taxiway Surface......11
2.3.6 Rapid Exit Taxiway......11
2.3.7 Taxiway Shoulders......11
2.3.8 Taxiway Strip......12
2.3.9 Taxiway Minimum separation distance......12
2.3.10 Taxiway Bearing Strength......12
2.4 Related Works......13
Chapter 3: Methodology......14
3.1 Research Design......14
3.2 Background Theory......14
3.3 Structure from Genetic Algorithm......16
3.3.1 Initialization......18
3.3.2 Reproduction......18
3.3.3 Evaluation......20
3.3.4 Selection......21
3.4 Genetic Algorithm for Optimization Taxi Route......22
3.5 Parameter Input......23
3.6 Data Input......24
Chapter 4: Result and Discussion......28
4.1 Result......28
4.2 Total Taxi time on 100 iteration......29
4.3 Before and After Optimization Route......39
Chapter 5: Conclusion and Recommendation......44
5.1 Conclusions......44
5.2 Recommendation......44
References......46
Extended Abstract......48

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