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J.M.Y. Leung¹, D.S.W. Lai², Y.-H. Kuo³ and H.K.F. Cheung¹

¹Systems Engineering and Engineering Management Department, The Chinese University of Hong Kong, Hong Kong
²Department of Information, Logistics and Innovation, VU University Amsterdam, The Netherlands
³Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong

doi:10.4203/ccp.110.287

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J.M.Y. Leung, D.S.W. Lai, Y.-H. Kuo, H.K.F. Cheung, "Real-Time Integrated Re-scheduling for Public Transit", in J. Pombo, (Editor), "Proceedings of the Third International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 287, 2016. doi:10.4203/ccp.110.287

Keywords: public transit, re-scheduling, stochastic.

Summary

The research described in this paper is motivated by the operations of a public transit company in Hong Kong. We investigate how real-time information can be utilized in combination with historical data to improve the controllers' routing and scheduling decisions practically. A dynamic and integrated vehicle and crew scheduling problem is introduced with the following characteristics: 1) The travel times are stochastic and time-dependent, and its realizations are only revealed during the execution of the plan. 2) The schedule can be revised when updated information is provided or when unexpected events occur. The objective is to maximize the route frequencies and mileage in order to provide good service to passengers, and simultaneously minimize overtime and mealbreak delays for motormen. To mitigate unexpected delays due to uncertainties in operations, various mathematical models are proposed for revising the schedules in real-time under a rolling-horizon framework. The efficiency and the effectiveness of the formulations are evaluated via simulation using real-world data.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 110 PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 287 Real-Time Integrated Re-scheduling for Public Transit J.M.Y. Leung¹, D.S.W. Lai², Y.-H. Kuo³ and H.K.F. Cheung¹ ¹Systems Engineering and Engineering Management Department, The Chinese University of Hong Kong, Hong Kong ²Department of Information, Logistics and Innovation, VU University Amsterdam, The Netherlands ³Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong doi:10.4203/ccp.110.287 purchase the full-text of this paper Full Bibliographic Reference for this paper J.M.Y. Leung, D.S.W. Lai, Y.-H. Kuo, H.K.F. Cheung, "Real-Time Integrated Re-scheduling for Public Transit", in J. Pombo, (Editor), "Proceedings of the Third International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 287, 2016. doi:10.4203/ccp.110.287 Keywords: public transit, re-scheduling, stochastic. Summary The research described in this paper is motivated by the operations of a public transit company in Hong Kong. We investigate how real-time information can be utilized in combination with historical data to improve the controllers' routing and scheduling decisions practically. A dynamic and integrated vehicle and crew scheduling problem is introduced with the following characteristics: 1) The travel times are stochastic and time-dependent, and its realizations are only revealed during the execution of the plan. 2) The schedule can be revised when updated information is provided or when unexpected events occur. The objective is to maximize the route frequencies and mileage in order to provide good service to passengers, and simultaneously minimize overtime and mealbreak delays for motormen. To mitigate unexpected delays due to uncertainties in operations, various mathematical models are proposed for revising the schedules in real-time under a rolling-horizon framework. The efficiency and the effectiveness of the formulations are evaluated via simulation using real-world data. purchase the full-text of this paper (price £22) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £85 +P&P)
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