整合跑道使用之機門指派問題

在機場的空側部分包含兩大部分的運作，機門指派與跑道使用，此兩部分的運作息息相關、互相影響，而空側的運作是影響機場服務水準的關鍵，不僅影響了旅客對機場的滿意程度，也影響了整個機場的容量，對於機場未來的發展也佔有重要的影響能力。根據過往機門指派問題的相關文獻中，文獻都著重在機門的指派上面，沒有問題將機門與跑道做綜合性的考慮。因此，本研究的機門指派問題整合了機門與跑道的使用，在機場現有的基礎設施下（機門數量、跑道數量），已知班機的起飛與降落班表，透過模式的指派，可以找到尖峰時刻時機門上是否還有空閒時間來服務更多班機，藉此希望可以提升機場空側的效率並提升機場的容量。本研究利用時空網路的技巧，將機場空側部分的指派轉換成零壹的整數規劃數學模式，且因為時空網路的節點與節線隨著欲指派模擬的時間增長而迅速地成長，因此本研究使用基因演算法來使得求解效率更快。最後，本研究將模式套入兩個案例分析，分別是臺北松山國際機場以及臺灣桃園國際機場，可以發現松山機場目前的容量是足夠的，若旅客量及飛機起降量提升也是有足夠的空間容納。然而，桃園機場在尖峰時刻面臨了機門短缺，又因為兩條跑道設施的關係使得兩條跑道無法獨立運作，影響了跑道的容量。根據案例的分析，本研究提出了結論與建議供後續研究參考。

關鍵字

機門指派；跑道容量；時空網路；基因演算法

並列摘要

The assignment of flights over gates and runways can be critical for the operation of an airport, which affects its capacity, scheduling and deployment of the associated airlines, and consequently the level of service to passengers. The assignment problem can be complicated because of numerous possible usage patterns over the spatiotemporal combinations of facility occupation, especially when there exists the dependence between runways and gates and/or runways themselves. However, such dependence has been rarely discussed in the literature. As a result, this study proposed an analytical framework to model comprehensive assignment over both gate assignment and runway usage. The time-space network was designed to present the operation framework. The mathematical binary integer programing was formulated to solve the problem. However, the number of time nodes in the time-space network increases rapidly, causing great computational inefficiency. Therefore, genetic algorithm is approached to solve this problem much more effectively and efficiently. Two case studies on Taipei Songshan Airport (TSA) and Taoyuan International Airport (TPE) are applied to the model in this research. Empirical case studies indicated that the developed model can help airport to assign the flights and find out the idle time on gate to serve more additional flights under current infrastructure layout. For the airport which suffer the congestion or shortage on gate, the model can be also be used to solve the problem.

並列關鍵字

gate assignment ； runway capacity ； time-space network ； genetic algorithm

參考文獻

Lu, H. A. (2001), “Optimized airport gate reassignment for delayed flights”, Transportation Planning Journal, Vol. 30, No. 4, pp. 849-870.

Tang, C. W., and Wang, W. C. (2012), “Gate assignments considering connections between arrival and departure flights at the taiwan taoyuan international airport”, Journal of the Chinese Institute of Transportation, Vol. 24 No. 3, pp. 305 – 330.

Dorndorf, U., Drexl, A., Nikulin, Y., and Pesch, E. (2007), “Flight gate scheduling: State-of-the-art and recent developments”, Omega, Vol. 35, No. 3, pp. 326-334.

Gu, Y., and Chung, C. A. (1999), “Genetic algorithm approach to aircraft gate reassignment problem”, Journal of Transportation Engineering, Vol. 125, No. 5, pp. 384-389.

Hou, Y. C. (2007), An Approach for Dynamic Airport Gate Assignments for Stochastic Flight Delays, Master Thesis, National Central University, Department of Civil Engineering.

國際替代計量

整合跑道使用之機門指派問題

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