Customized bus service design for jointly optimizing passenger-to-vehicle assignment and vehicle routing |
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Affiliation: | 1. School of Electronic and Information Engineering, Beihang University, Beijing 100091, China;2. National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beijing 100091, China;3. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China;4. School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287, USA;1. Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, United States;2. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiaotong University, China;3. School of Civil and Environmental Engineering, University of New South Wales, Australia |
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Abstract: | Emerging transportation network services, such as customized buses, hold the promise of expanding overall traveler accessibility in congested metropolitan areas. A number of internet-based customized bus services have been planned and deployed for major origin-destination (OD) pairs to/from inner cities with limited physical road infrastructure. In this research, we aim to develop a joint optimization model for addressing a number of practical challenges for providing flexible public transportation services. First, how to maintain minimum loading rate requirements and increase the number of customers per bus for the bus operators to reach long-term profitability. Second, how to optimize detailed bus routing and timetabling plans to satisfy a wide range of specific user constraints, such as passengers’ pickup and delivery locations with preferred time windows, through flexible decision for matching passengers to bus routes. From a space-time network modeling perspective, this paper develops a multi-commodity network flow-based optimization model to formulate a customized bus service network design problem so as to optimize the utilization of the vehicle capacity while satisfying individual demand requests defined through space-time windows. We further develop a solution algorithm based on the Lagrangian decomposition for the primal problem and a space-time prism based method to reduce the solution search space. Case studies using both the illustrative and real-world large-scale transportation networks are conducted to demonstrate the effectiveness of the proposed algorithm and its sensitivity under different practical operating conditions. |
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Keywords: | Customized buses Space-time network Vehicle routing problem Generalized assignment problem Ridesharing |
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