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姓名 陳宇軒(Yu-Hsuan Chen)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 整合航空客運與貨運之飛航排程暨班次表建立之研究
(An Integrated Model Combine Passengers and Freight for Airline Fleet Routing and Timetable Planning)
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摘要(中) 飛航排程對航空業者營運影響甚鉅,其排程之結果不但攸關設備之使用效率、左右班次表之擬訂與人員之調度,更重要的,將進而直接影響及業者之獲利能力、服務水準與市場之競爭能力等。近年來,航空公司在機型上除使用客、貨機以外,開始有使用客貨兩用的機型,其可同時支援客機與貨機的排程規劃。然目前國內業者在實務作業上,主要仍以人工及試誤的方式,規劃客機、貨機及客貨機之排程。做法上首先擬定出客機與客貨機的飛航排程,再根據初擬的客貨機排程,考量市場潛在的貨物需求,進行貨機的排程規劃。繼而修正原先初擬之客貨機排程,以此反覆試誤方式,求得客機、貨機與客貨機三者最終可行之班次表與飛航排程。由於此方法不具系統性分析,以致無法有效掌握客機、貨機與客貨機排程間之相關性,因此其排程之效率常易隨系統規模之增大而降低,進而導致營運績效之不佳。
緣此,本研究以航空業者立場,在給定的營運資料下,包括機隊規模、航權、可用時間帶、相關飛航成本等,以營運利潤最大化為目標,並考量相關營運限制,構建一整合客機、貨機與客貨機的飛航排程模式。此模式能於未來實務的應用上,提供航空業一短期排程暨班次表建立之輔助規劃工具。本研究利用網路動技巧構建模式,模式中含有多個人流、物流與機流時空網路,以定式旅客、貨物與飛機在時空中的流動情況。此模式可定式為一整數多重貨物網路流動問題,屬NP-hard問題,尤其是應用於實際問題時,規模甚為龐大,在求解上更難於以往傳統之飛航排程規劃問題。為有效求解大規模問題,本研究利用拉氏鬆弛法暨次梯度法、網路單體法、及自行發展之啟發式解法,配合數學規劃軟體CPLEX求解模式。最後,為測試模式及求解演算法之績效,本研究以一國籍航空公司之營運資料為例,進行測試與分析,進而提出結論及建議。
摘要(英) Fleet routing and flight scheduling are important in airline operations. They always affect the usage efficiency of facilities and crew scheduling. Furthermore, they are essential to carriers’ profitability, level of service and competitive capability in the market. Recently, besides passenger flights and cargo flights, some airlines introduced combi flights in their flight scheduling. The combi flights combine passengers and cargos in one flight and can supple passenger flights and cargo flights during a carrier’s regular operation. However, the carriers in Taiwan currently adopt a try-and-error method to determine the schedules of passenger flights, cargo flight and combi flights. The method starts by manually determining the passenger and combi flight schedules together. Based on the passenger and combi flight schedules and the projected cargo demand, the cargo flight schedule is then determined. Thereafter, the combi flight schedule is modified by considering the cargo flight schedule and the passenger flight schedule is revised in accordance with the combi flight schedule. The process is repeated until the final fleet routing and timetables are obtained. Since such a method without systemic analyses cannot effectively manage the interrelationship among the passenger, cargo and combi flight schedules, the performance of the obtained schedules would easily decrease as the system scale is enlarged. As a result, the operating performance could possibly be inferior.
Therefore, given the operating data, including fleet size, airport flight quota and available time slots, related flight cost, on the basis of the carrier’s perspective, this research tries to develop a scheduling model by integrating passenger, cargo and combi flight schedules, with the objective of maximizing the operating profit, subject to the related operating constraints. The model is a useful planning tool for airlines to determine a suitable fleet routing and timetables in their short-term operations. We employ network flow techniques to construct the model, which include passenger-flow, cargo-flow and fleet-flow networks in order to formulate the flows of passengers, cargos and fleet in the dimensions of time and space. The model is formulated as an integer multiple commodity network flow problem that is characterized as an NP-hard problem. Since the real problem size is huge, this model is harder to solve than the conventional passenger flight scheduling problems in the past. A Lagrangian relaxation-based algorithm, coupled with a subgradient method, the network simplex method and a heuristic for upper bound solution, is suggested to solve the problem. Finally, to evaluate the model and the solution algorithm, we perform a case study by using the real operating data from a major Taiwan airline.
關鍵字(中) ★ 拉氏演算法
★ 多重貨物網路流動問題
★ 時空網路
★ 客貨機
★ 飛航排程
關鍵字(英) ★ Lagrangian relaxation-based algorithm
★ fleet routing
★ combi flight
★ time-space network
★ multiple commodity network flow problem
論文目次 第一章 緒論 1
1.1研究背景與動機 1
1.2研究目的與範圍 2
1.3研究方法與程式架構 3
第二章 文獻回顧 4
2.1短期航空排程相關文獻 4
2.2分解式演算法(DECOMPOSITION ALGORITHM)求解模式相關文獻 7
2.3小結 10
第三章 模式構建 11
3.1模式假設 11
3.2模式架構 13
3.2.1網路設計考量因素 13
3.2.2機流時空網路 16
3.2.3人流時空網路 22
3.2.4物流時空網路 25
3.2.5排程營運限制 28
3.3數學定式 29
3.3.1符號說明 29
3.3.2數學定式 30
3.4小結 33
第四章 求解演算法設計 34
4.1 演算法一(FF) 35
4.1.1 目標值下限 36
4.1.2 目標值上限解 39
4.1.3 收斂機制 45
4.2 演算法二(PF) 47
4.3單機定線 53
4.4 其他演算法說明 54
4.5 小結 54
第五章 實例研究 55
5.1 輸入資料 55
5.1.1航線資料 55
5.1.2機場起降時間帶及航權限制 57
5.1.3航機種類及機隊規模 59
5.1.4起迄資料 60
5.1.5成本資料 61
5.1.6運價資料 63
5.2 輸出資料 64
5.2.1 實例結果輸出 64
5.2.2 測試例結果輸出 68
5.3 單機定線 75
5.4 敏感度分析 77
5.4.1 票價 77
5.4.2 旅次需求 81
5.5 小結 85
第六章 結論與建議 86
6.1結論 86
6.2 建議 87
6.3 貢獻 87
參考文獻 88
附錄一 CPLEX CALLABLE LIBRARY CODE 91
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指導教授 顏上堯(Shang-Yao Yan) 審核日期 2004-7-16
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