機場行李卸載轉盤指派問題之研究;The Airport Luggage Loading Carousel Assignment Problem

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Title:	機場行李卸載轉盤指派問題之研究;The Airport Luggage Loading Carousel Assignment Problem
Authors:	洪逸樺;Hong, Yi-Hua
Contributors:	土木工程學系
Keywords:	行李卸載轉盤;基因演算法;2-OPT區域搜尋;行李分揀系統;共用資源指派;Luggage loading carousel;Genetic algorithm;2-OPT;Baggage handling system;Common use resource assignment
Date:	2017-12-01
Issue Date:	2018-01-16 10:13:04 (UTC+8)
Publisher:	國立中央大學
Abstract:	在開拓新航點與航線多元發展下，桃園國際機場正積極為成為東亞地區轉運樞紐做準備。除了機場捷運開通以及興建第三航廈計畫外，目前第二航廈也做了許多更新，包含整合各項軟硬體設備、跑道整建工程等，其中出境部分直線型行李卸載道也於2015年更新成轉盤型行李卸載轉盤，期能提高作業效率。隨著桃園國際機場航空運量大幅成長，每天有超越10萬件以上的行李需處理運送，但目前實務上作法仍仰賴人工經驗進行行李運送規劃，缺乏系統性整合，容易造成資源浪費。因此本研究在參考航班運量預報資訊，並考量實務問題之複雜度，建構出機場行李卸載轉盤指派之模式。本研究利用數學規劃方法，在滿足所有航班皆指派至一行李卸載轉盤和實務方面限制為前提下，以追求最小化航班行李卸載轉盤重疊作業時間為目標，構建機場行李卸載轉盤指派之模式。在求解方法上，因模式問題規模龐大，本研究發展一啟發式演算法，利用撰寫基因演算法並搭配2-OPT區域搜尋法求解問題。而為評估模式之實用性，本研究以國內某國際機場為例進行範例測試，並針對不同參數進行敏感度分析，結果顯示本研究提出之模式在航班指派行李卸載轉盤上能有效規劃，故本研究之模式與求解演算法可提供決策單位作為航班指派行李卸載轉盤規劃之參考。;Taoyuan International Airport is actively preparing to become a transit hub in East Asia by expanding new routes. In addition to activating the airport MRT and the construction of third terminal, the existing second terminal is also going to update such as various hardware, software and runway construction projects. Among those, the straight-line baggage conveyor in the departure section had been updated to baggage loading carousel in 2015, hoping to improve the efficiency. As the traffic at Taoyuan International Airport grows significantly and there are more than 100,000 pieces of luggage transported everyday, the current practice still depends on manual labor to perform the planning of luggage transportation which lacks systematic integration and causes resource waste. Therefore, this study refers to flight traffic forecast and considers the complexity of practical problems to construct an assignment model for luggage carousel at the airport. In this study we use the mathematical programming method to formulate a luggage carousel assignment model to minimize the overlapping time between flights. The proposed model is characterized as NP-hard. To solve the large scale problem efficiently, a genetic algorithm, coupled with a 2-OPT local search, is developed. Finally, a case study using real data from an international airport in Taiwan is performed to evaluate the model and the heuristic algorithm. The results show that the model and the algorithm are useful for assigning luggage carousel and decrease the overlapping time between flights efficiently.
Appears in Collections:	[Graduate Institute of Civil Engineering] Electronic Thesis & Dissertation

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