Two-phase stochastic program for transit network design under demand uncertainty |
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| Institution: | 1. Institute of Transport Studies, Department of Civil Engineering, Monash University, Melbourne, Australia;2. Department of Transport and Planning, Delft University of Technology, Delft, Netherlands;1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China;2. Urban Planning and Transportation Group, Eindhoven University of Technology, Eindhoven, the Netherlands;3. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China;4. Department of Industrial Engineering, Tsinghua University, Beijing, China;1. Institute of Transportation Engineering, Zhejiang University, Hangzhou, Zhejiang 310058, China;2. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 999077, China;3. Department of Civil and Coastal Engineering, University of Florida, Gainesville, FL 32611, United States;1. Division of Computer Science, University of Nottingham Ningbo China, Ningbo 315100, China;2. Department of Business and Management Science, Norwegian School of Economics, NO-5045 Bergen, Norway;3. Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo 315100, China;4. Department of Computer Science and Mathematics, University of Stirling, Stirling FK9 4LA, UK |
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| Abstract: | This paper develops a reliability-based formulation for rapid transit network design under demand uncertainty. We use the notion of service reliability to confine the stochastic demand into a bounded uncertainty set that the rapid transit network is designed to cover. To evaluate the outcome of the service reliability chosen, flexible services are introduced to carry the demand overflow that exceeds the capacity of the rapid transit network such designed. A two-phase stochastic program is formulated, in which the transit line alignments and frequencies are determined in phase 1 for a specified level of service reliability; whereas in phase 2, flexible services are determined depending on the demand realization to capture the cost of demand overflow. Then the service reliability is optimized to minimize the combined rapid transit network cost obtained in phase 1, and the flexible services cost and passenger cost obtained in phase 2. The transit line alignments and passenger flows are studied under the principles of system optimal (SO) and user equilibrium (UE). We then develop a two-phase solution algorithm that combines the gradient method and neighborhood search and apply it to a series of networks. The results demonstrate the advantages of utilizing the two-phase formulation to determine the service reliability as compared with the traditional robust formulation that pre-specifies a robustness level. |
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