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研究生:施昺羲
研究生(外文):Shih, Ping Hsi
論文名稱:機場行李運輸系統航班卸載道指派問題
論文名稱(外文):Airport Baggage Handling System Unloading Zone Allocation
指導教授:林則孟林則孟引用關係
指導教授(外文):Lin, Tse Meng
學位類別:碩士
校院名稱:國立清華大學
系所名稱:工業工程與工程管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:中文
論文頁數:72
中文關鍵詞:機場行李運輸系統航班卸載道指派問題基因演算法
外文關鍵詞:Airport Baggage Handling SystemUnloading Zone AllocationGA
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  • 被引用被引用:7
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桃園機場二航廈航班數量的增長,行李運輸系統中卸載道數目已不敷使用,因此將進行升級工程將原本同一時段只可卸載一航班的直線型卸載道改變為轉盤型卸載道,轉盤型卸載道容量較大,可同時卸載多個航班,得以解決卸載道不足的問題。
在改變為轉盤型卸載道後,航班的安排將成為一個重要的議題,若安排的不好將導致轉盤需同時卸載多個航班,不僅會導致轉盤上的行李量過多,使轉盤耗損,更會使得地勤人員難於辨識不同航班的行李而提高分揀錯誤的風險,導致行李無法正確的送上飛機。
本研究將提出以最小化卸載道重疊時間為目標,在將所有航班都排入卸載道卸載的前提下,求出最佳的航班卸載道配置,以降低同時段下轉盤上的行李量及航班數量,以方便地勤人員作業及維持轉盤的使用情形。而由於本問題之求解空間較大,若以數學解進行搜尋,將耗費大量時間,因此本研究提出以基因演算法進行求解,並改良舊有隨機產生起始解的方法,改以各航班之起飛時間為依據先行安排卸載道,在透過隨機突變得方式產生其餘起始解,有效的縮短收尋時間及求解品質。
為了更貼近現實情形,本研究亦考量系統具隨機性之情形,並透過對歷史資料之分析,求得行李卸載時間受航空公司、航班目的地與乘客數及航班起飛時間三個因素所影響,因此依照三種因素進行分類,求出各組的卸載處理時間之分配(distribution),並以此為卸載時間依據進行隨機型之實驗,再加入OCBA以減少運算時間,有效率的求出一航班卸載道指派結果。

The most important issue of airport baggage handling system (BHS) is to transport the baggage to the plane on time and correctly. The mishandling of baggage is a critical problem to airport and airlines. With the strong growth of the flight, the unloading area in Taiwan Taoyuan International Airport (TPE) is no longer enough. To increase the number of processible flights in the unloading zone, TPE will change the unloading belt lateral to carousel. Carousel has bigger capacity which is enough to carry the baggage of more than two flights. With this change TPE can dealing with the problem of capacity not enough.
More than one flight arranged to the same carousel may have overlapping of their unloading period. When the carousel is arranged too much flights which of their unloading period is overlapping, it will make the ground staff hard to separate the baggage of different flight, and will also make the carousel overladen. To avoid this situation happening, the arrangement of the flight unloading zone should be very careful.
In this paper, we propose “Overlapping Time” as the main performance of unloading zone allocation problem. Under the premise that all the flights are allocated to a carousel, find the best allocation to reduce the working loading of ground staff. Due to the complicate of this problem, we propose to use Genetic Algorithm (GA) to generate the allocation.
To be more similar to the real system, we consider the stochastic of the flight unloading period. The unloading period will be affected by the airline constrain, the destination of the flight, and the baggage number of the flight. According to this three factors, we separated all the weekly flight into different groups, and figure out the distribution of their unloading period. Using this distribution to generate the unloading period of different flights and using Optimal Computing Budget Allocation (OCBA) to efficiently find the optimal allocation of flight unloading zone.

目錄
第一章 緒論
1.1研究背景與動機
1.2研究目的
1.3研究範圍與限制
1.4研究步驟
第二章 文獻回顧
2.1機場行李運輸系統
2.2機場航班卸載道指派
2.3基因演算法
2.4粒子演算法(Particle Swarm Optimization)
2.5資源分配最佳化(Optimal Computing Budget Allocation)
第三章 航班卸載道指派問題分析
3.1問題定義與模式建構
3.2模式驗證
3.3研究方法
3.4實驗與分析
3.4.1 GA與PSO之演算法比較
3.4.2 GA之參數分析
3.4.3起始解之產生方式改良
3.4.4卸載道指派限制探討
3.4.5北候機廊廳卸載道使用數量探討
第四章 隨機性下之航班卸載道指派問題分析
4.1問題定義
4.2航班資料分析
4.3研究方法
4.3.1 基因演算法與OCBA
4.3.2 基因演算法與OCBA之流程
4.4實務案例實驗與分析
4.4.1模擬最佳化方法之參數校準
4.4.2確定型問題與隨機型問題之比較
第五章 結論與建議
5.1結論
5.2建議與未來方向


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