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Determining optimal frequency and vehicle capacity for public transit routes: A generalized newsvendor model
Institution:1. Northeastern University, Boston, MA02115, U.S.A;2. Massachusetts Institute of Technology, Cambridge, MA02139, U.S.A;1. Department of Transport and Planning, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, The Netherlands\n;2. Department of Transport Science, KTH Royal Institute of Technology, Stockholm, Sweden;1. Istituto di Calcolo e Reti ad Alte Prestazioni, Consiglio Nazionale delle Ricerche, Rende, Italy;2. HEC Montréal, 3000 chemin de la Côte-Sainte-Catherine, Montréal, H3T 2A7, Canada;1. Consiglio Nazionale delle Ricerche, Istituto di Calcolo e Reti ad Alte Prestazioni, via P. Bucci, Rende, Italy;2. Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Canada;3. Università della Calabria, Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, via P. Bucci, Rende, Italy;4. HEC Montréal, 3000 chemin de la Côte-Sainte-Catherine, Montréal H3T 2A7, Canada
Abstract:The level of service on public transit routes is very much affected by the frequency and vehicle capacity. The combined values of these variables contribute to the costs associated with route operations as well as the costs associated with passenger comfort, such as waiting and overcrowding. The new approach to the problem that we introduce combines both passenger and operator costs within a generalized newsvendor model. From the passenger perspective, waiting and overcrowding costs are used; from the operator’s perspective, the costs are related to vehicle size, empty seats, and lost sales. Maximal passenger average waiting time as well as maximal vehicle capacity are considered as constraints that are imposed by the regulator to assure a minimal public transit service level or in order to comply with other regulatory considerations. The advantages of the newsvendor model are that (a) costs are treated as shortages (overcrowding) and surpluses (empty seats); (b) the model presents simultaneous optimal results for both frequency and vehicle size; (c) an efficient and fast algorithm is developed; and (d) the model assumes stochastic demand, and is not restricted to a specific distribution. We demonstrate the usefulness of the model through a case study and sensitivity analysis.
Keywords:Public transit  Frequency  Vehicle size  Non-linear optimization  Newsvendor model
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