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DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 朱致遠(James C. Chu) | |
dc.contributor.author | Yao-Jen Chang | en |
dc.contributor.author | 張耀仁 | zh_TW |
dc.date.accessioned | 2021-06-15T16:35:11Z | - |
dc.date.available | 2020-08-21 | |
dc.date.copyright | 2020-08-21 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-08-06 | |
dc.identifier.citation | Pachauri, R. K., Allen, M. R., Barros, V. R., Broome, J., Cramer, W., Christ, R., ... Dubash, N. K. (2014). Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change (p. 151). Ipcc. United Nations Environment Programme. (2019) Emissions Gap Report 2019. Lu, C. T. (2013). Applying transtheoretical model to identify factors affecting highway passenger carriers’ electric vehicle usage (master's thesis, National Chiao Tung University, Taiwan). Lai, W. T. (2017). An analysis of operational benchmarks, financial benefits and development strategies for electric urban buses. Transportation Planning Journal, 46(4), 377-397. Yeh, J. C. (2019). Optimization of scheduling and charging of electric buses using discrete-event simulation (master's thesis, National Taiwan University). Wen, M., Linde, E., Ropke, S., Mirchandani, P., Larsen, A. (2016). An adaptive large neighborhood search heuristic for the electric vehicle scheduling problem. Computers Operations Research, 76, 73-83. Paul, T., Yamada, H. (2014, October). Operation and charging scheduling of electric buses in a city bus route network. In 17th International IEEE Conference on Intelligent Transportation Systems (ITSC) (pp. 2780-2786). IEEE. Li, J. Q. (2014). Transit bus scheduling with limited energy. Transportation Science, 48(4), 521-539. Wang, Y., Huang, Y., Xu, J., Barclay, N. (2017). Optimal recharging scheduling for urban electric buses: A case study in Davis. Transportation Research Part E: Logistics and Transportation Review, 100, 115-132. Hiermann, G., Puchinger, J., Ropke, S., Hartl, R. F. (2016). The electric fleet size and mix vehicle routing problem with time windows and recharging stations. European Journal of Operational Research, 252(3), 995-1018. Gao, S., Zhang, P. P., Tan, D. R., Zhang, X. L. (2013). The research on electric bus operation intelligence scheduling model and algorithm. In Applied Mechanics and Materials (Vol. 253, pp. 1330-1334). Trans Tech Publications Ltd. Rogge, M., van der Hurk, E., Larsen, A., Sauer, D. U. (2018). Electric bus fleet size and mix problem with optimization of charging infrastructure. Applied Energy, 211, 282-295. Macrina, G., Pugliese, L. D. P., Guerriero, F., Laporte, G. (2019). The green mixed fleet vehicle routing problem with partial battery recharging and time windows. Computers Operations Research, 101, 183-199. Sebastiani, M. T., Lüders, R., Fonseca, K. V. O. (2016). Evaluating electric bus operation for a real-world BRT public transportation using simulation optimization. IEEE Transactions on Intelligent Transportation Systems, 17(10), 2777-2786. Swisher, J. R., Hyden, P. D., Jacobson, S. H., Schruben, L. W. (2004). A survey of recent advances in discrete input parameter discrete-event simulation optimization. Iie Transactions, 36(6), 591-600. Swisher, J. R., Hyden, P. D., Jacobson, S. H., Schruben, L. W. (2000, December). A survey of simulation optimization techniques and procedures. In 2000 Winter Simulation Conference Proceedings (Cat. No. 00CH37165) (Vol. 1, pp. 119-128). IEEE. Swisher, J. R., Jacobson, S. H., Yücesan, E. (2003). Discrete-event simulation optimization using ranking, selection, and multiple comparison procedures: A survey. ACM Transactions on Modeling and Computer Simulation (TOMACS), 13(2), 134-154. Amaran, S., Sahinidis, N. V., Sharda, B., Bury, S. J. (2016). Simulation optimization: a review of algorithms and applications. Annals of Operations Research, 240(1), 351-380. Ministry of Transportation and Communication R.O.C. (2011). Management guideline of public transport subsidy for electric bus. Transportation Bureau of Kaohsiung City Government. (2019). Bus route operation overview of Kaohsiung City. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52942 | - |
dc.description.abstract | 為了降低燃油運具排放廢氣所造成的汙染,許多國家已將運具電動化納入減碳目標當中,其中具有公共運具特性的電動公車也在這波潮流下被大力提倡。然而受限於電池所能營運的里程數,充電行為需要被納入電動公車排班調度的考量當中。本研究考慮多場站與多路線下混合車種與充電樁的電動公車系統,建立離散事件模擬模式以模擬電動公車系統的排班調度;此外本研究亦建立多層相容性離散事件模擬模式,在最小化總成本的目標下求得最佳化的車輛充電樁組合,並產出派車與充電之排程。本研究亦分析不同電動公車營運策略的成效,並建立一組指標以提升排班調度的彈性與對於規則的量化評估。透過上述模擬測試與策略分析,最終提供電動公車系統在購置、營運與管理上的建議。 | zh_TW |
dc.description.abstract | Electric buses have been promoted as a decarbonizing transit mode to reduce the emission of exhaust gas from the vehicle in numerous countries worldwide. However, due to the limitation of battery capacity for electric bus, the recharging constraints would greatly affect the scheduling issue. Considering the multiple depots and routes with heterogeneous buses and chargers, this research conducted the discrete event simulation model to simulate the operation of electric bus system. The model is capable to construct a more detailed, flexible, and comprehensive system that approximates to the actual operation. Multiple Compatibility Layer Optimization Simulation Approach was formulated to find the optimal combination with minimum total cost. The model can further generate the dispatch and charge schedule. Additionally, several operation strategies are examined for effectiveness and a set of rule indices is formulated to enhance the scheduling flexibility and rule evaluation. This research eventually provides recommendations for the electric bus system on the aspect of acquisition, operation, and management. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T16:35:11Z (GMT). No. of bitstreams: 1 U0001-0508202016431500.pdf: 1932511 bytes, checksum: 1628eb846a4fa6185a18f70717121524 (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 誌謝 i 摘要 ii ABSTRACT iii CONTENT iv LIST OF FIGURES vi LIST OF TABLES vii Chapter 1 Introduction 1 1.1 Background Information and Motivation 1 1.2 Research Objective 3 1.3 Research Domain 3 1.4 Research Structure 4 Chapter 2 Literature Review 5 2.1 Electric Vehicle Scheduling Problem 5 2.2 Mixed Electric Vehicle Routing Problem 8 2.3 Simulation Optimization 10 2.4 Summary of Literature Review 12 Chapter 3 Methodology 14 3.1 Problem Statement 14 3.2 Discrete Event Simulation 16 3.2.1 Entity 17 3.2.2 Queues and Resource 17 3.2.3 Main Process 19 3.2.4 Event 22 3.3 Simulation Optimization 31 Chapter 4 Case Study 36 4.1 Database Construction 36 4.1.1 Route Database 36 4.1.2 Bus Information 40 4.1.3 Charger Information 41 4.1.4 Other Information 41 4.2 Result Demonstration 42 4.3 Analysis of Operation Strategy 49 4.3.1 Diesel Bus and E-Bus 49 4.3.2 Route Bound and Mixed Use 54 4.3.3 Homogeneous and Heterogeneous Bus and Charger 59 4.4 Index Evaluation 65 4.4.1 Rule Analysis 66 4.4.2 Index Formulation 71 4.4.3 Rule Evaluation 75 Chapter 5 Conclusion and Future Work 84 5.1 Conclusions 84 5.2 Suggestions 85 REFERENCES 87 | |
dc.language.iso | en | |
dc.title | 考量混合車種與充電樁下電動公車派車與充電排程之模擬最佳化 | zh_TW |
dc.title | Scheduling of Electric Bus Dispatching and Charging with Heterogeneous Fleet and Chargers using Simulation Optimization Approach | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 水敬心(Chin-Sum Shui),沈宗緯(Chung-Wei Shen) | |
dc.subject.keyword | 電動公車,混合使用,排班調度,離散事件模擬,模擬最佳化, | zh_TW |
dc.subject.keyword | Electric bus,Heterogeneous,Scheduling,Discrete event simulation,Simulation optimization, | en |
dc.relation.page | 90 | |
dc.identifier.doi | 10.6342/NTU202002485 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2020-08-07 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
顯示於系所單位: | 土木工程學系 |
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