臺灣博碩士論文加值系統

本研究求解單一路線大眾運輸系統之時變發車頻率問題：在給定路網、車隊規模與動態、隨機乘客抵達率條件下，求解此一大眾運輸系統每單位時間的服務率。於研究中首先以逐點流體基礎近似方法(Point-wise Fluid-Based Approximation Approach)建構單一路線動態大眾運輸等候網路(Dynamic Transit Queuing Network, DTQN)模型，接著將此模型與最佳化數學規劃模型整合，在考慮兩個不同的目標下：最小化總系統成本(營運成本與等候成本)與最小化總系統成本加上碳排放成本，求解這兩個不同的問題模式，而且所求解的時變發車頻率必須介於交通主管機關所訂之最大班距與給定車隊規模所能提供之最小班距間。本研究根據台北市公車路線資料產生接近實際狀況之測試例題，利用GAMS的MINOS求解器求解此測試例題之最佳時變發車頻率，並分析改變乘客抵達率與目標式各成本項權重對發車頻率、等候人數與各成本項目的影響。研究結果發現：時變服務率與各站等候人數都隨著整體抵達率增加而增加；考慮碳排放成本會使得發車頻率降低，等候成本的變化則與營運成本變化成反比。

This study deals with the frequency (the reciprocal of headway) setting problem for a single transit route, given its stops, fleet, and dynamic, stochastic passenger arrival rates. The objective is to obtain optimal time-varying frequencies in terms of the service rate (or number of available seats) per time unit which can be used to derive the multiple headways in the planning horizon. A point-wise fluid-based approximation approach is adopted to construct a single route dynamic transit queuing network (DTQN) that describes the single transit route system. The DTQN is the encapsulated in an optimization model that determines optimal time-varying frequencies with respect to a certain objective and subject to the minimal and maximal headway requirements set by the fleet size and the government agency, respectively. This study considers two different objectives: the first one is to minimize total system cost (including operational and waiting costs), the second being the first plus carbon emission cost. A test problem instance was designed based on a bus route in Taipei city, and the MINOS solver of GAMS was applied to solve for the optimal time-varying frequencies with respect to the above two different objectives. The sensitivity analyses were also conducted to examine the impacts of passenger arrival rates and weights of the cost components in the objective function on the frequency, waiting cost, and operational cost.

摘要 i
Abstract ii
目 錄 iii
表目錄 v
圖目錄 vi
第一章 緒論 1
1.1 研究動機與目的 1
1.2 問題描述 4
1.3 研究方法與流程 5
第二章 文獻回顧 7
2.1 目標函數從整體系統角度考量 7
2.2 目標函數從營運者角度考量 11
2.3 目標函數從乘客角度考量 12
2.4 逐點流體基礎近似方法 14
2.5 小結 17
第三章 最佳時變發車頻率之數學模式 19
3.1 動態大眾運輸系統等候網路 20
3.2 時變發車頻率最佳化數學模式 23
3.2.1 問題描述 23
3.2.2 數學模式建構 25
第四章 數值實驗與敏感度分析 27
4.1 實驗設計 27
4.2 改變依時抵達率之求解結果 30
4.2.1 模式1 31
4.2.2 模式2 35
4.3改變目標式權重值之求解結果 39
4.3.1 模式1 39
4.3.2 模式2 43
4.4結果彙整 47
4.4.1 抵達率變動 47
4.4.2 成本權重變動 48
第五章 結論與建議 50
5.1 結論 50
5.2 未來研究方向建議 51
參考文獻 52

[1]周義華、吳宗憲，公車路線間相互支援之排班專家系統，運輸計劃季刊，第二十六卷，第一期，1997，第159-202 頁。
[2]周義華、張國揚，公車網路班次分派與車輛配置之研究，運輸計畫季刊，第 十八卷，第二期，1989，第223-254頁。
[3]周義華、謝金玫，專家系統應用於公車排班作業之研究，運輸計劃季刊，第二十三卷，第二期，1995，第199-234 頁。
[4]林則孟，系統模擬理論與應用，台中市：滄海書局，2001。
[5]邱裕鈞、劉邦政，社會福利最大化之大眾運輸補貼雙層數學規劃模式－考量生態足跡限制，碩士論文，國立交通大學交通運輸研究所，新竹，2010。
[6]柯志明，具排班功能之公車系統模擬產生器的設計，碩士論文，中原大學工業工程研究所，桃園，2004。
[7]張有恆，現代運輸學 第二版，台北：華泰文化股份有限公司，2009。
[8]張有恆，運輸管理 第三版，台北：華泰文化股份有限公司，2010。
[9]張學孔、許哲瑋，管制情況下多時段公車費率與服務水準之設計，碩士論文，國立台灣大學土木工程研究所，台北，1996。
[10]陳明典，市區公車行車系統模擬軟體之設計，碩士論文，中原大學工業工程研究所，桃園，2001。
[11]陳武正、蕭耀廷，公車車輛調度模擬分析，運輸計劃季刊，第七卷，第四期，1978，第10-20頁。
[12]陳政信，公車多班距時刻表設計的隨機最佳化問題，碩士論文，中原大學工業工程研究所，桃園，2002。
[13]馮正民、徐瑞彬，以社會經濟與土地使用因素探討台北都會區總體旅運型態，碩士論文，國立交通大學交通運輸研究所，新竹，2001。
[14]劉方旗，市區公車排班與即時機動調度之研究─以新竹客運為例，碩士論文，國立交通大學交通運輸研究所，新竹，1998。
[15]歐信宏，國道客運轉運系統車輛排班模式之研究，博士論文，國立成功大學交通管理學系，台南，2002。
[16]韓復華，客運系統班次排定問題之研究，碩士論文，國立台灣大學土木工程學研究所，台北，1976。
[17]A. Rindos, S. Woolet, I. Viniotis, and K. S. Trivedi, "Exact methods for the analysis of nonhomogeneous continuous time Markov Chains," Numerical Methods for Markov Chains, Chapter 8, ed. W. Stewart, Elsevier, 1995.
[18]A.F. Han and N.H.M. Wilson, "The allocation of buses in heavily utilized networks with overlapping routes," Transportation Research Part B, vol.16, 1982, pp. 221-232.
[19]B. Yu, Z. Yang and J. Yao, "Genetic algorithm for bus frequency optimization," Journal of Transportation Engineering, vol. 136, no. 6, June 2010, pp. 576-583.
[20]C.L. Richard and R.O. Amedeo, Urban Operations Research, Prentice-Hall, Englewood Cliffs, N. J., 1981, pp. 132-136.
[21]F.J.M. Salzborn, "Optimum bus scheduling," Transportation Science, vol.6, no. 2, 1972, pp. 137-148.
[22]F.J.M. Salzborn, "Scheduling bus systems with interchanges," Transportation Science, vol.14, no. 3, 1980, pp. 211-220.
[23]G. Desaulniers and M.D. Hickman, Handbooks in Operations Research and Management Science, vol.14: Transportation, North Holland: Elsevier Science, 2007, pp. 69-127
[24]H.F. Chen, "Stochastic optimization in computing multiple headways for a single bus line," Journal of Chinese Institute of Industrial Engineers, vol. 24, no. 5, 2007, pp. 351-359.
[25]H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe,2006 IPCC Guidelines for National Greenhouse Gas Inventories Volume2 Energy, Japan: Institute for Global Environmental Strategies (IGES), 2006, pp. 1.21.
[26]I. Constantin and M. Florian, "Optimizing frequencies in a transit network: a nonlinear bi-level programming approach," International Transportation Operation Research, vol. 2, no.2, 1995, pp. 149-164.
[27]L. Green and P. Kolesar, "The pointwise stationary approximation for queues with nonstationary arrivals," Management Science, vol.37, no.1, 1991, pp. 84-97.
[28]P.G. Furth and N.H.M. Wilson, "Setting frequencies on bus routes: theory and practice," Transportation Research Record, vol. 818, 1982, pp. 1-7.
[29]R. E. Rosenthal, GAMS — A User''s Guide, GAMS Development Corporation, Washington, DC, USA, 2006.
[30]S. Chowdhury and S. Chien, "Optimization of transfer coordination for intermodal transit networks," Proceedings of the 80th Annual Meeting, Transportation Research Board, Washington, DC, 2001.
[31]S. Scheele, "A supply model for public transit services," Transportation Research Part B, vol.14, 1980, pp. 133-146.
[32]S.J. Lin and N.C. Shih, "The characteric analysis of energy consumption and SOx、NOx、CO2 road transportation sector in Taiwan," Bureau of Energy, Ministry of Economic Affairs, Taipei, 2001.
[33]S.J. Park, Bus network scheduling with genetic algorithms and simulation, Master’s Thesis, University of Maryland, USA, 2005.
[34]S.Y. Yan, C.J. Chi and C.H. Tang, "Inter-city bus routing and timetable setting under stochastic demands," Transportation Research Part A vol. 40, 2006, pp. 572-586.
[35]V. Guihaire and J.K. Hao, "Transit network design and scheduling: a global review," Transportation Research Part A: Policy and Practice, vol. 42, no. 10, December 2008, pp. 1251-1273.
[36]V.M. Tom and S. Mohan, "Transit route network design using frequency coded genetic algorithm," Journal of Transportation Engineering, vol. 129, no. 2, 2003, pp. 186-195.
[37]W. Kim, B. Son, J.H. Chung, E. Kim, "Development of Real-Time Optimal Bus Scheduling and Headway Control Models," Transportation Research Record: Journal of the Transportation Research Board, vol. 2, 2009, pp 33-41.
[38]W.P. Wang, D. Tipper and S. Banerjee, "A simple approximation for modeling non-stationary queues," IEEE, Fifteenth Annual Joint Conference of the IEEE Computer Societies, Networking the Next Generation: INFOCOM ''96. vol. 1, 1996, pp. 255-262.
[39]Z.Y. Gao, H.J. Sun, and L.L. Shan, "A continuous equilibrium network design model and algorithm for transit systems," Transportation Research Part B, vol. 38, 2004, pp. 235-250.