An Integrated Strategy for Rescheduling High-Speed Train Operation under Single-Direction Disruption
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Published:2023-08-29
Issue:17
Volume:15
Page:13040
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ISSN:2071-1050
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Container-title:Sustainability
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language:en
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Short-container-title:Sustainability
Author:
Han Chang1ORCID, Zhou Leishan1, Guo Bin12, Yue Yixiang12, Zhao Wenqiang1, Wang Zeyu3ORCID, Zhou Hanxiao4ORCID
Affiliation:
1. The School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China 2. Frontiers Science Center for Smart High-Speed Railway System, Beijing Jiaotong University, Beijing 100044, China 3. Infrastructure Investment Co., Ltd., Beijing 100101, China 4. Zhejiang Rail Transit Operation Management Group Co., Ltd., Hangzhou 310020, China
Abstract
Comparing to other modes of transportation, high-speed railway has the advantages of energy saving, environment friendly, safety and convenience for passengers, and has been more and more popular. However, unforeseen emergencies may disrupt the normal train operation. In this paper, an integrated dispatch strategy (IDS) is proposed to synergistically reschedule the train timetable and rolling stock circulation plan under single-direction disruptions. A two-objective model is formulated, aiming at minimizing both the delay time of passengers and the operation costs of railway companies, to reschedule the train operation efficiently and economically. An algorithm based on Non-dominated Sorting Genetic Algorithms-II (NSGA-II) is designed to solve the model. To accelerate the solving process, we propose a quick method to generate an assignment plan to serve disrupted passengers, and based on the practical experiences, the algorithm acceleration strategy (AAS) is proposed to improve the quality of initial solutions. The model and algorithm are tested on real-world instances of the Beijing-Shanghai high-speed railway line. The results indicate that the average minimized delay time of passengers is 6,012,386 min and the average minimized additional operation costs (operation mileage of standby rolling stocks) are 1623 km, with a decrease of 28.5% and 18.3%, respectively, indicating the model and algorithm are adaptable to handle single-direction disruptions on the railway line, and AAS can further accelerate the computing speed and improve the solutions quality. Finally, the characteristics of disrupted sections of railway lines are well studied and analyzed.
Funder
Research Supported by the Fundamental Research Funds for the Central Universities Research project of China State Railway Group Co., Ltd. Research project of China Railway Beijing Group Co., Ltd.
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
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