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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/53426

Title: 考量SKYPOOLING平台下航空公司裝載設備調度與規模之研究
Airline unit load device dispatching considering SKYPOOLING platform
Authors: Chu, Pao-Ying
朱寶瑩
Contributors: NTOU:Department of Transportation Science
國立臺灣海洋大學:運輸科學系
Keywords: 裝載設備;調度;SKYPOOLING;二項分布;達成率;配對成功率;區間估計;預計數量;真實數量
Unit load device;dispatching;SKYPOOLING;binomial distribution;achievement rate;pairing success rate;interval estimation;estimated quantity;real quantity
Date: 2019
Issue Date: 2020-07-02T08:25:58Z
Abstract: 航空公司裝載設備(Unit Load Device,簡稱ULD)包括貨盤與貨櫃,是航空公司每日營運不可或缺的重要設備。航空公司良好的ULD調度能有效提高ULD使用效率並降低ULD持有的規模。目前,SKYPOOLING平台是航空公司間ULD共享營運的一個新的免費平台,航空公司透過參與SKYPOOLING平台,可以相互借用ULD與請他航協助運送(即一般所稱協運),其目的即是希望透過共享的機制,能有效降低航空公司所需持有的ULD規模。另外,目前業者在SKYPOOLING運作上,每週會將所需借用與協運的ULD數量於平台上提出需求,但是在提出需求時並無考量SKYPOOLING借用與協運的成功配對率,此舉忽略預期借用與協運的數量於實際營運時的達成性,往往使得預期規劃的數量過於樂觀,造成原預期規劃結果與真實結果產生落差,降低SKYPOOLING的功效。有鑑於此,本研究考慮SKYPOOLING借用與協運之達成率,在業者希望之規劃達成率下,進行ULD的調度規劃。亦即本研究考慮SKYPOOLING借用與協運之規劃達成率、成功配對機率、借用與協運之預計與真實數量,以幫助業者規劃一滿足SKYPOOLING規劃達成率下的ULD調度規劃,以有效降發揮SKYPOOLING運作功效並降低業者ULD持有的規模。 本研究結合數學規劃中的時空網路與統計學中的二項分布與區間估計,建構一非線性混合整數模式。其中,時空網路用以定式各型ULD於各場站與時間之流動情形。另外,運用二項分布計算ULD借用與協運的達成率,以反應SKYPOOLING借用與協運之預計與真實數量。同時本研究亦利用區間估計技巧,以樣本成功配對機率估計母體成功機率之區間,將此區間加入模式之中,並將區間之下限與上限機率視為悲觀與樂觀情形,以進行分析。此外,本研究發展一反覆迭代啟發式求解演算法,利用分解式概念將模式分為不考慮達成率與考慮達成率之兩個子問題,之後再以基因改善機制求得改善解,再將求得之解反覆迭代回兩個子問題進行求解。最後,以國內航空公司資料為例進行分析,並根據研究的結果,提出結論與建議。
The Unit Load Device (ULD), including pallets and containers, is essential equipment for the airline's daily operations. A good ULD scheduling by airlines can effectively improve ULD usage efficiency and reduce the size of ULD holdings. Currently, the SKYPOOLING platform is a new free platform for ULD sharing operations between airlines. By participating in the SKYPOOLING platform, airlines can borrow ULD from each other and ask for assist in transportation, the purpose of which is to reduce the size of ULD that airlines need to hold by this sharing mechanism. However, the airline will put the demand on the platform every week, but it does not consider the successful matching rate of SKYPOOLING, which ignores the achievement of the number of the association's operations in actual operations. Thus, it makes the number of expected plans too optimistic, resulting in a gap between the original expected planning results and the real results, reducing the effectiveness of SKYPOOLING. In view of this, this study considers the achievement rate of SKYPOOLING borrowing and the cooperation and performs the scheduling planning of ULD under the planning achievement rate that the industry hopes. That is to say, this study considers the SKYPOOLING borrowing and the cooperation planning achievement rate, the successful matching probability, the borrowing, and the forecast and the actual quantity of the cooperation, to help the industry plan to meet the ULD scheduling plan under the SKYPOOLING planning achievement rate, effectively reduce the SKYPOOLING. It works and reduces the size of the industry's ULD holdings. This study combines the binomial distribution and interval estimation in statistics and the time-space network in mathematical programming to construct a nonlinear mixed-integer model. Among them, the time-space network is used to determine the flow of various types of ULDs at each station and time. In addition, the binomial distribution used to calculate the achievement rate of ULD borrowing and cooperation, in order to reflect the expected and actual number of SKYPOOLING borrowing and cooperation. At the same time, this study also uses the interval estimation technique to estimate the probability of maternal success rate by the successful pairing probability of the sample, adding this interval to the model, and considers the lower limit of the interval and the upper limit probability as pessimistic and optimistic for analysis. In addition, this study develops a repeated iterative heuristic algorithm, which uses the concept of decomposition to divide the model into two sub-problems that do not consider the achievement rate and the achievement rate. We will apply the decomposition concept and the searching mechanism in a Genetic Algorithm to develop an iterated solution algorithm. We will perform a case study using the real operating data from a Taiwan airline. Finally, conclusions and suggestions will be given.
URI: http://ethesys.lib.ntou.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=G0010768006.id
http://ntour.ntou.edu.tw:8080/ir/handle/987654321/53426
Appears in Collections:[運輸科學系] 博碩士論文

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