考量列車迴轉與擾動因子情況下高速鐵路系統最佳化排班設計之研究

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研究生：	費瑞拉 Nailah Firdausiyah
論文名稱：	考量列車迴轉與擾動因子情況下高速鐵路系統最佳化排班設計之研究 Timetabling Optimization Design Considering Train Circulation and Disturbances for High-Speed Rail System
指導教授：	周建成 Chien-Cheng Chou
口試委員:
學位類別：	碩士 Master
系所名稱：	工學院 - 土木工程學系 Department of Civil Engineering
畢業學年度：	98
語文別：	英文
論文頁數：	117
中文關鍵詞：	時刻表、最佳化模式、環狀列車、敏感度分析
外文關鍵詞：	sensitivity analysis, train circulation, timetable, optimization model
相關次數：	點閱：7 下載：0
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高速列車的管理工作包含例行維修(如車輛迴轉以清理)與災害發生時之應變措
施等，由於高速列車中上述管理工作非常重要，台灣高鐵公司雖然已有相關列車班表模型，但是此模型尚未完整，因此，基於相關的文獻回顧，其他學者並沒有針對環狀的列車系統，例如列車的迴轉運作等，這些運作在台灣高鐵是非常重要的。本研究根據台灣高鐵的相關需求與運作方式提出一個最佳化排班模式，結合整數與動態規劃並使用CPLEX 軟體求其最佳解，當鐵道發生災害時，高鐵單位會對鐵路系統重新排程，所以本研究的模式亦支援重新排程的最佳化。本研究應用敏感度分析針對不同的參數觀察目標值的影響，參考台灣高鐵的列車資料，使用兩線軌道、128 服務、29 輛列車與8 個車站，經由實驗結果表示，本研究所求得的最佳解與高鐵公司的時刻表一致(程式執行時間為0.10 秒)，因此，此模式可以應用模擬並分析相關的列車系統，提供災害發生時即時的決策支援。

Managing circulation of trains, including regular inspection, car cleaning times and turning back operations, has become important due to the scarcity of railway company
resources. The Taiwan High-Speed Railway (THSR) already has cyclic patterns of daily train circulation, but these patterns have not been modeled yet. Moreover, based on a review of the literature, researchers in the railway field have never considered train circulation, especially in
HSR systems, even though it is important. This research proposes a scheduling optimization model that has the capability to accommodate not only basic requirements such as railway topology, traffic rules, and user requirements, but also train circulation as well. Mixed integer
and dynamic programming have been chosen to solve the model under CPLEX. In addition, railway systems are often characterized by high traffic density and heterogeneous traffic that is sensitive to disturbances; thus, rescheduling activity for updating an existing schedule in response to disruptions is needed. This research has applied sensitivity analysis in order to identify how disturbances propagate in the original timetable and which actions to decide in order to mitigate the impact instead of cancelling many trains. Assumptions as well as input and output values are configured by using real data from THSR,which used two lines, 128 services, 29 trains, and eight stations. The model has obtained a timetable result as good as the real timetable in a short computation time (that is, 0.10 second). Sensitivity analysis results could determine critical infrastructure and parameters that are
sensitive to disturbances. Therefore, it could be a good simulation analysis for predicting the effect of disruptions on the timetable without doing real experiments such as trains being disordered and overtaken.

摘要 ......................................................i
ABSTRACT................................................. ii
ACKNOWLEDGEMENTS........................................ iii
TABLE OF CONTENTS........................................ iv
LIST OF TABLES.......................................... vii
LIST OF FIGURES........................................ viii
CHAPTER 1 INTRODUCTION.............................................. 1
1. Background and Motivation............................ 1
2. Research Objectives.................................. 4
3. Research Scope and Limitations....................... 5
4. Research Methodology................................. 7
4.1. Conduct literature review.......................... 8
4.2. Characterize train scheduling and timetable components ............................................... 8
4.3. Develop model ..................................... 9
4.4. Collect and input data............................. 9
4.5. Solve and analyze model........................... 10
4.6. Check the model................................... 10
4.7. Draw conclusions and recommendations.............. 11
5. Structure of Report................................. 11
CHAPTER 2 LITERATURE REVIEW.............................. 12
1. Railway Planning.................................... 12
2. Optimization Model.................................. 13
2.1. Basic Concept and Numerical Method................ 14
2.2. Solver Software................................... 17
3. Sensitivity analysis................................ 18
4. Timetable Activities................................ 19
4.1. Scheduling........................................ 19
4.1.1. Characteristic and rules........................ 20
4.1.2. Train scheduling process in THSR system......... 24
4.2. Rescheduling...................................... 26
4.2.1. Characteristic and rules........................ 26
4.2.2. Rescheduling process in THSR system............. 27
5. Related works....................................... 28
5.1. A heuristic for the train pathing and timetabling problem (Lee and Chen, 2009)............................. 29
5.2. Solution of real world train timetabling problems (Caprara, et al, 2001) .................................. 35
5.3. Mathematical solutions for solving periodic railway transportation (Salido and Federico, 2009)............... 37
5.4. Train rescheduling algorithm which minimizes passenger dissatisfaction (Norio,2005)................... 41
5.5. A constraint based interactive train rescheduling tool (Chiu, 2002) ....................................... 42
5.6. Heuristic approach to train rescheduling (Mladenovic, 2007) ................................................... 44
6. Summary of literature review........................ 45
CHAPTER 3 MODEL DEVELOPMENT.............................. 47
1. Problem Descriptions................................ 47
2. The proposed mathematical model..................... 50
2.1. Objective function................................ 50
2.2. Model variables, parameters, and constraints...... 50
2.3. Notations and Indexes............................. 53
3. Input file creation................................. 54
3.1. Software.......................................... 54
3.2. Database.......................................... 55
3.3. Model application................................. 65
CHAPTER 4 RESULTS AND MODEL CHECKING..................... 67
1. Model results....................................... 67
1.1. Algorithm to solve the model...................... 67
1.2. Timetable diagrams................................ 70
2. Model checking...................................... 72
3. Sensitivity analysis................................ 76
3.1. Sensitivity of the maximum operation times with respect to delay times................................... 76
3.2. Sensitivity of the maximum operation times with respect to allowed time margin........................... 82
3.3. Sensitivity of arrival times respect to maximum delay time .................................................... 83
CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS................ 88
1. Conclusions......................................... 88
2. Recommendations..................................... 89
3. Contributions....................................... 90
Appendix A: Model Application Instructions............... 91
BIBLIOGRAPHY............................................. 98

                                

Afonso, Pedro Alexandre de Carvalho. (2008). Railway traffic management. Ph.D Dissertation. Instito Superior Tecnico, Universidade Tecnica de Lisboa
Brannlund, U., P. O. Lindberg, A. & Nou, J.-E. Nilsson. (1998). Railway Timetabling Using Lagrangian Relaxation. Transportation Science. Vol. 32, No. 4, pp 358-369
Caprara, Alberto., et. al. (2001). Solution of Real-World Train Timetabling Problems in 34th Hawaii International Conference on System Sciences. Proceedings, HICSS-34. Vol. 3, pp 3030
Carley, M. Kathleen. (1996). Validating computational model. Office of Naval Research (ONR), United States Navy Grant No. N00014-93-1-0793
Castillo, Enrique, et al. (2008). Timetabling optimization of a single railway track line with sensitivity analysis. Sociedad de Estadistica e Investigacion Operativa, Top (2009), Vol.17, pp 256–287
Chiu, C. K. et.all. (2002). A Constraint-Based Interactive Train Rescheduling Tool. Kluwer Journal Academic Publishers. Vol. 7, pp 167–198
Cowling, P. & Johansson, M. (2002). Using real time information for effective dynamic scheduling. European Journal of Operational Research. Vol. 139(2), pp 230-244.
Diaz, B. Adenso. M. Oliva Gonzalez. & P. Gonzalez-Torre. (1998). On-line timetable rescheduling in regional train services. Transportation Research Part B 33, pp 387-398
Fornarino, Claude. (2009). ILOG : ottimizzazione e pianificazione. (shown at IMPACT: smart SOA conference. Milano, June 17th 2009). ftp://ftp.software.ibm.com/software/it/impact/presentazioni/ilog_ottimizzazione_e_pia
nificazione.pdf. (viewed on February, 26th 2010 )
Gabor, Maroti. (2006). Operations research models for railway rolling stock planning. Ph.D Dissertation. Eindhoven, Technische Universiteit Eindhoven
Higgins., E. Kozan. & L. Ferreira. (1996). Heuristic Techniques for Single Line Train Scheduling. Journal of Heuristic. Vol. 3, pp 43-62
Hughes. Ed. & Trevor Kearney. (2008). What is new in optimization with SAS/OR in SAS Global Forum. Paper 199
Huisman, D., et. al. (2005). Operations Research in Passenger Railway Transportation. Statistica Neerlandica, Vol. 59(4), pp 467-497
ILOG. (2001). ILOG Cplex 7.1, Reference Manual
ILOG. (2007). ILOG Cplex 11.0, User’s Manual
Kunimatsu, Taketoshi. (2006). Evaluation of train rescheduling alternatives using station service indices. Journal of Railway Technology Avalanche No. 14, pp 81
Lee, Yusin. & Chuen-Yih Chen. (2009). A heuristic for the train pathing and timetabling problem. Transportation Research Part B 43 (2009), pp 837-861
Luss, Hannan. & Moshe B. Rosenwein. (1997). Operations Research applications: Opportunities and accomplishments. European Journal of Operational Research 97(1997), pp 220-244
Mess, A.I. (1991). Railway scheduling by network optimization. Mathematical and Computer Modelling. Vol. 15, pp 33-42
Mladenovic, Snezana. & Mirjana Cangalovic. (2007). Heuristic approach to train rescheduling. Yugoslav Journal of Operations Research 17 (2007), Vol. 1, pp 9-29
Murty, G. Katta. (2003). Optimization models for decision making: Volume 1. Junior Level Self-Teaching Web-Book.
http://ioe.engin.umich.edu/people/fac/books/murty/opti_model/junior-0.pdf. (viewed on February, 26th 2010 )
Norio, Tomii, et. al. (2006). Train rescheduling algorithm which minimize passenger dissatisfaction. Railway Technical Research Institute. M. Ali and F. Esposito (Eds.):IEA/AIE 2006, LNAI 3633, pp 829-838
Railway Safety and Standard Board. (2006). The rail industry - a way forward on sustainable development. RSBB London. www.rssb.co.uk (viewed on February, 26th 2010)
Salido, Miguel & Federico Barber. (2009). Mathematical solutions for solving periodic railway transportation. Mathematical Problems in Engineering, Volume 2009, Article
ID 728916
Taiwan Shinkansen Corporation. (2007). Equipment and operational manual of THSR
Taiwan Shinkansen Corporation. (2007). System specification for operation function in THSR
Vieira, G.E., J.W. Herrmann and E. Lin. (2003). Rescheduling Manufacturing Systems: A Framework of Startegies, Policies, and Methods. Journal of Scheduling, Vol. 6, pp 39-
62
Yan, Shangyao. & Yu-Lin Shih. (2009). Optimal scheduling of emergency roadway repair and subsequent relief distribution. Computers & Operations Research Journal, Vol. 36,pp 2049-2066

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