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研究生:蔡松翰
研究生(外文):CAI,SONG-HAN
論文名稱:考量不同目標之綠色運具旅遊行程規劃 -以澎湖本島為例
論文名稱(外文):Travel Itinerary Planning with Different Objectives Using Green Carriers: A Study Case of Penghu Main Island
指導教授:柯博仁柯博仁引用關係
指導教授(外文):KE,BWO-REN
口試委員:陳鴻誠、吳培基
口試委員(外文):CHEN,HONG-CHENG、WU,PEI-CHI
口試日期:2022-01-24
學位類別:碩士
校院名稱:國立澎湖科技大學
系所名稱:電機工程系電資碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:66
中文關鍵詞:綠色運具、旅遊行程規劃、最佳化、基因演算法、人工蜂群演算法
外文關鍵詞:green vehicle、itinerary planning、optimization、genetic algorithm、artificial bee colony algorithm
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  本論文以澎湖本島為例,從事單人旅客旅程規劃與多人綠色運具選擇最佳化,全部僅使用綠色運具(電動機車、電動公車、共享單車與步行)進行低碳環保旅遊,以達到能源消耗、旅程時間與建置成本最小化的目的。研究中以全島32處景點、22處電動機車電池充電站、24處電動機車電池交換站、15條公車路線及各路線站牌為基礎設施,並假設22處共享單車租賃站設置地點於電池充電站附近。
  單人旅程規劃利用基因演算法配合旅行銷售員問題進行最佳化,以電動機車與步行,進行景點順序排程,求解最佳旅遊路線。多人綠色運具選擇利用單人旅程規劃的最佳旅遊路線為基礎,使用三種交通工具與步行的不同組合,包含1. 電動機車、公車與步行,2. 電動機車、共享單車與步行,3. 電動機車、公車、共享單車與步行,分別使用基因演算法與人工蜂群演算法進行綠色運具選擇最佳化,以達到降低能源消耗、旅程時間與建置成本的目的。
  經研究發現,在多人綠色運具選擇的能源消耗最小化中,使用案例1A能源消耗最小化的旅遊路線為基礎,加入電動機車與共享單車為最佳組合,因騎乘共享單車不需消耗能量,對降低能耗有很大幫助。在多人綠色運具選擇的旅程時間最小化中,使用案例1A能源消耗最小化的旅遊路線為基礎,加入電動機車與公車為最佳組合。電動機車與公車每公里能源消耗相近,而搭乘公車需等待時間,因此騎乘機車較節省旅程時間。在多人綠色運具選擇的建置成本最小化中,使用案例1B旅程時間最小化的旅遊路線為基礎,加入電動機車與公車為最佳組合,並且發現能耗較高時,建置成本降低。

  This paper presents the optimization of solo travel itinerary planning and multipassenger green vehicle selection on the main island of the Penghu islands. Only walking and green vehicles (e.g., electric scooters, electric buses, and shared bicycles) were considered so as to minimize energy consumption, travel time, and setup cost. The 32 attractions, 22 electric scooter battery charging stations, 24 electric scooter battery exchange stations, and 15 bus routes and bus stops on each route across the island were the infrastructure of focus in this study. The shared bicycle rental stations, 22 in total, were assumed to be installed nearby the battery recharge stations.
  Solo travel itinerary planning was optimized through the genetic algorithm in addressing the traveling salesman problem. The travels to the attractions on foot and on electric scooters were arranged in sequence to identify the optimal travel route. On the basis of the optimized travel route, 3 combinations of green vehicle travels and walking were implemented: (1) scooter, bus, and walking; (2) scooter, shared bicycle, and walking; (3) scooter, bus, shared bicycle, and walking. The selection of green vehicles was optimized through the genetic algorithm and the artificial bee colony algorithm to minimize energy consumption, travel time, and setup cost.
  Route 1A was adopted as the basis of minimizing energy consumption, and the optimal combination of green vehicles involved the use of electric scooters and shared bicycles. Because shared bicycles do not consume energy, they are conducive to minimizing energy consumption. Route 1A was also adopted as the basis for minimizing travel time, and the optimal vehicle combination for the purpose involved the use of scooters and buses. Scooters and buses are nearly identical in the energy they consume per km, but riding buses requires waiting. Therefore, scooters are the most time-efficient option. Route 1B, which is the route for minimizing travel time, was adopted for the purpose of minimizing setup cost; the optimal vehicle combination involved the use of scooters and buses. Notably, increasing energy consumption led to a decrease in setup cost.

摘要 I
ABSTRACT II
誌謝 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
1.1 研究動機 1
1.2 文獻回顧 2
1.3 章節概要 4
第二章 澎湖本島景點與綠色運具介紹 5
2.1 澎湖本島景點、電池充/換電站、公車站牌、共享單車租賃站 5
2.2 電動機車租賃與電能補充方式 7
2.2.1 電動機車租賃系統 7
2.2.2 電池充電與交換方式 7
2.3 公車運輸系統 8
2.4 共享單車租賃系統 9
2.5 步行參數 10
第三章 綠色運具運行模擬與相關參數 11
3.1 單人電動機車運行模擬 11
3.2 多人綠色運具運行模擬 14
3.2.1 使用電動機車與電動公車 16
3.2.2 使用電動機車與共享單車 19
3.2.3 使用電動機車、公車與共享單車 22
第四章 最佳化方法 26
4.1 基因演算法(Genetic Algorithm) 26
4.2 人工蜂群演算法(Artificial Bee Colony) 28
第五章 研究結果 30
5.1 案例1:單人綠色運具運行規劃—使用電動機車 30
5.1.1 案例1A:能源消耗最小化 31
5.1.2 案例1B:旅程時間最小化 31
5.1.3 案例1C:建置成本最小化 31
5.2 案例2:多人綠色運具選擇規劃—使用電動機車與公車 32
5.2.1 案例2A:能源消耗最小化 32
5.2.1 案例2B:旅程時間最小化 34
5.2.2 案例2C:建置成本最小化 36
5.3 案例3:多人綠色運具選擇規劃—使用電動機車與共享單車 38
5.3.1 案例3A:能源消耗最小化 38
5.3.2 案例3B:旅程時間最小化 40
5.3.3 案例3C:建置成本最小化 42
5.4 案例4:多人綠色運具選擇規劃—使用電動機車、公車與共享單車 44
5.4.1 案例4A:能源消耗最小化 45
5.4.2 案例4B:旅程時間最小化 46
5.4.3 案例4C:建置成本最小化 48
第六章 結論與未來研究方向 51
6.1 結論 51
6.2 未來研究方向 52
參考文獻 53
附錄 57

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