博碩士論文 973202079 詳細資訊




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姓名 謝潤曉(Jun-hsiao Hsieh)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 跨校選授課專車排程規劃之研究
(Inter-school Bus Schedule Planning)
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摘要(中) 近年來隨著台灣地區大專院校數量的增加,相對地學生人數與之劇增,各校間教學合作日益頻繁,校際間之選授課行為也因應而生,台灣聯合大學系統即為最佳範例。現行之跨校選授課專車,目的在於服務台灣聯合大學系統之教職員與學生,但跨校選授課專車之班表為人工經驗排班方式進行規劃,因缺乏系統性分析,故無法完善地服務搭乘需求。緣此,本研究針對跨校選授課專車之特性,以學校立場為考量,構建一系統最佳化模式,以期能提供學校方面作為有效規劃之輔助工具,並協助決策者有效地進行規劃。
本研究利用網路流動之技巧與數學規劃方法,建立一考量多對多起迄需求之跨校選授課專車排程模式,以最小車輛數及最小總加權營運時間為目標,於網路設計上,加上時窗限制以滿足實務之營運條件。本研究之模式為含額外限制之多目標整數網路流動問題,屬NP-hard問題,為有效率地求解大規模之問題,本研究利用問題分解策略,且配合CPLEX數學規劃套裝軟體,發展一有效之啟發式解法。最後評估本研究模式與啟發式解法之實用績效,以台灣聯合大學系統為範例測試,並針對不同之參數進行敏感度分析與方案分析,其測試結果良好,最後提出結論與建議。
摘要(英) In recent years, with the increasing of universities in Taiwan, the number of students rises as a result. With this situation, the behavior of having inter-school classes appears. The University System of Taiwan is the best example. Nowadays, the inter-school bus is set up to service the teachers and students of The University System of Taiwan, but the schedule is manually performed by planning personnel with experience in current practice. Without a systematic analysis, it cannot satisfy the demands perfectly. Therefore, in this research, consider the properties of the inter-school bus problem and based on the perspective of school planner, we develop a system-optimized model. The model is expected to be an effective tool for the school, also, it can help planner to solve problems.
In this research, we employed network flow techniques and mathematical programming method, and build an inter-school bus scheduling model with many-to-many OD demand. The minimum number of vehicles and the minimum total weighted operating time is our target. In the network design, adds time window limit to meet the practical operating. Model is formulated as an integer multiple commodity network flow problem, which is characterized as NP-hard. To efficiently solve the problems whose sizes are expected to be huge in real practice, we developed a heuristic algorithm by use the problem decomposition strategy with CPLEX software. In addition, to evaluate the performance of inter-school bus model and solution algorithm practice, we take the University System of Taiwan as an example. Performing sensitive and scenario analysis for different parameters, and the result of the model test shows good. Finally, conclusions and suggestions are given.
Key words: Inter-school bus, Time-space network, Heuristic, Multiple commodity network flow problem.
關鍵字(中) ★ 跨校選授課專車
★ 含額外限制網路流動問題
★ 時空網路
★ 啟發解法
關鍵字(英) ★ Inter-school bus
★ Time-space network
★ Heuristic
★ Multiple commodity network flow problem
論文目次 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 研究背景與動機 1
1.2 研究目的與範圍 3
1.3 研究方法與程式架構 4
第二章 文獻回顧 6
2.1校車排程與路線設計相關文獻 6
2.1.1國外校車規劃與排程 6
2.1.2國內校車規劃與排班 8
2.1.3國內外校車規劃小結 9
2.2 時窗限制之車輛派遣與排程問題 10
2.3 撥召共乘相關文獻 11
2.4 時空網路設計相關文獻 14
2.4.1海空運方面 14
2.4.2陸運方面 15
2.5大型含額外限制之整數網路流動問題啟發式演算法 16
2.6文獻評析 19
第三章 模式構建 20
3.1跨校選授課專車排程模式 20
3.1.1基本假設與已知資訊 20
3.1.2時空網路設計 22
3.1.3符號說明 29
3.1.4數學定式 30
3.2 模式應用 31
3.3 小結 32
第四章 求解演算法設計 33
4.1啟發式解法 33
4.2目標值下限解 37
4.3車輛定線與乘客配對演算法 38
4.4 小結 38
第五章 範例測試 39
5.1資料分析 39
5.1.1 跨校選授課專車排程規劃所需之相關參數資料 39
5.1.2 搭乘需求之資料 40
5.1.3 跨校專車排程規劃之成本資料 42
5.2模式發展 43
5.2.1 問題規模 43
5.2.2 模式輸入資料 43
5.3電腦演算環境及設定 44
5.3.1 電腦演算環境 44
5.3.2 相關參數設定 45
5.3.3 模式輸出資料 46
5.4測試結果與分析 46
5.5敏感度分析 48
5.5.1總搭乘需求人數之敏感度分析 48
5.5.2 ODT種類之敏感度分析 53
5.5.3發車成本值之敏感度分析 57
5.5.4旅行成本值之敏感度分析 58
5.5.5人流未服務之懲罰成本值之敏感度分析 62
5.6 方案分析 63
5.6.1 不同問題規模之方案分析 63
5.6.2 發車地點固定與不固定之方案分析 66
5.6.3 現行班表之方案分析 68
5.7 小結 69
第六章 結論與建議 70
6.1結論 70
6.2建議 71
6.3貢獻 72
參考文獻 73
附錄 81
附錄一 CPLEX Callable Library Code 81
附錄二 ODT種類輸入資料 82
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78. Xiang, Z., Chu, C., and Chen, H., “A fast heuristic for solving a large-scale static dial-a-ride problem under complex constraints,” European Journal of Operational Research, Vol. 174, pp. 1117-1139 (2006).
79. Yan, S. and Young, H. F., “A Decision Support Framework for Multi-Fleet Routing and Multi-Stop Flight Scheduling,” Transportation Research, Vol. 30A, pp. 379-398 (1996).
80. Yan, S. and Chen, H. L., “A Scheduling Model and a Solution Algorithm for Inter-city Bus Carriers,” Transportation Research, Vol. 36A, pp. 805-825 (2002).
81. Yan, S., Chi, C. J. and Tang, C. H., “Inter-city Bus Routing and Timetable Setting under Stochastic Demands,” Transportation Research A 40, pp.572-586 (2006).
82. Yan, S. and Shih, Y. L., “A Time-Space Network Model for Work Team Scheduling after a Major Disaster,” Journal of the Chinese Institute of Engineers, Vol. 30, No. 1, pp. 63-75. (2006)
83. Yan, S. and Tang, C. H., “A heuristic approach for Airport Gate Assignments for Stochastic Flight Delays,” European Journal of Operational Research, Vol. 180, Iss. 2, pp. 547-567 (2007).
84. Yan, S. and Chen, C. H., “Coordinated flight scheduling models for allied airlines,” Transportation Research Part C, Vol. 15, pp. 246-264(2007).
85. Yan, S., Tang, C. H., and Fu, T.C., “An airline scheduling model and solution algorithms under stochastic demands,” European Journal of Operational Research, Vol. 190, pp. 22-39(2008).
86. Yan, S., Lai, W., and Chen, M., “Production scheduling and truck dispatching of ready mixed concrete,” Transportation Research, Part E, Vol. 44, Issue 1, pp. 164-179(2008).
87. Zhu, K., Tan, K.C. and Lee, L.H., “Heuristic methods for vehicle routing problem with time windows,” Artificial Intelligence in Engineering, 15(3), pp. 281-295(2000).
指導教授 顏上堯(Shang-Yao Yan) 審核日期 2010-7-16
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