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|Keywords: ||時間帶;飛航排程;變動需求;旅客選擇模式;非線性混合整數規劃問題;次要市場交易;time slot;fleet routing;variable demand;passenger choice model;nonlinear mixed integer program;secondary trading|
|Issue Date: ||2014-10-15 14:22:48 (UTC+8)|
;Fleet routing and flight scheduling are important in the field of airline operations. In order to create a brilliant flight schedule for an airline, the fleet and its supply, related operating requirements, restrictions on practice, and customers’ response on its service should be taken into account. Last but not least, the most important part is that airline could acquire the ideal slots in the airport or not. In this paper, based on the airline’s perspective, given the operating data, including fleet size, airport flight quota, and related flight cost, the objective is to maximize the operating profit and build a short-term flight scheduling model with slot allocation and variable demands. If the airline wants to improve the flight schedule with secondary slot trading, this model would analyze whether the rented slots or the swapped slots would be profitable for airlines. New flight schedule and the profit for the airline would be displayed within this model. The model will also provide assistance in planning to construct their short-term flight schedules and timetables for airlines.
This paper employed network flow techniques to construct the model which includes fleet flow network and multiple passengers network. For fleet flow network design, it is assumed that time slot location has been known, and we applied integer flow networks to formulate the aircraft routes in terms of time and space. In the passenger flow networks, considering the loss of waiting passengers in real case, this paper introduced a passenger choice model to formulate passenger flows. Constraints between the fleet flow and passenger flow network were considered to fulfill the real operating requirements. The model is a mixed integer non-linear programming problem that is characterized as a NP-hard problem and is more difficult to be solved than traditional flight scheduling problems that are often formulated as integer linear programs. To solve the model with practical size problems efficiently, we developed an iterative solution framework which will repeatedly modify the target airline market share in iteration and solve a fixed-demand flight scheduling problem. We used certain country of airports data and related operating data of domestic passenger transportation from some airlines to analyze. The test results show this model that to be effective and that the solution method could be useful in practice.
|Appears in Collections:||[土木工程研究所] 博碩士論文|
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