Journal
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
Volume 84, Issue -, Pages 31-44Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.omega.2018.04.003
Keywords
Urban railway transit; Last train timetabling; Bus bridging service management; Mixed integer linear programming; Decomposition method
Funding
- China National Funds for Distinguished Young Scientists [71525002]
- NSFC [71771018, 71621001]
- Research Foundation of State Key Laboratory of Rail Traffic Control and Safety [RCS2018ZZ003]
- Austrian Federal Ministry of Science, Research and Economy within the EURASIA PACIFIC UNINET framework
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Urban railway transit systems are not only the main source of city trips but also provide important support for city operations. In this study, we address the last train timetable optimization and bus bridging service problem in the context of urban railway transit networks. By exploiting problem-specific knowledge, we present an optimization-based approach that deals with the issue of last-train passengers being stranded at midnight by developing a last train and bus bridging coordination mixed integer linear programming (MILP) model. Due to the large problem size, an effective decomposition method is developed for solving the real-world and large-scale problems, which decomposes the original MILP into two smaller MILP models: maximizing last train connections and minimizing waiting times for rail-to-bus passengers. In addition, we prove that this decomposition method can solve the original MILP to global optimality. Finally, we apply the developed MILP models to the Vienna Subway to assess the effectiveness of the proposed approaches and conduct sensitivity analyses of the bus fleet size involved in the last train timetable optimization and bus bridging service problem. (C) 2018 Elsevier Ltd. All rights reserved.
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