Integrated public transport timetable synchronization with vehicle scheduling

In public transport (PT) operations planning, timetable synchronization is a useful strategy to reduce inter-route or inter-modal passenger transfer waiting time and provide a well-connected service. This work addresses the integrated PT timetable synchronization with vehicle scheduling problem for...

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Bibliographic Details
Published in:Transportmetrica (Abingdon, Oxfordshire, UK) Vol. 13; no. 10; pp. 932 - 954
Main Authors: Liu, Tao, Ceder, Avishai (Avi), Chowdhury, Subeh
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 26.11.2017
Taylor & Francis Ltd
Subjects:
bi-objective integer programming
deficit function
Integer programming
Mathematical models
Pareto optimization
Passengers
Production scheduling
Public transport
Public transportation
Scheduling
Synchronism
timetable synchronization
Timetables
vehicle scheduling
ISSN:2324-9935, 2324-9943
Online Access:Get full text
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Summary:In public transport (PT) operations planning, timetable synchronization is a useful strategy to reduce inter-route or inter-modal passenger transfer waiting time and provide a well-connected service. This work addresses the integrated PT timetable synchronization with vehicle scheduling problem for a given PT network. A new bi-objective integer programming model is developed for the problem. The objectives are to maximize the number of simultaneous vehicle arrivals at the transfer nodes of a PT network, and to minimize the required fleet size. A novel two-stage deficit function (DF)-based method is developed to solve the mathematical model using a human-machine interactive approach. At the first stage, some existing optimizers are employed to quickly generate an initial solution. At the second stage, a DF-based graphical optimization technique is utilized to generate alternative Pareto-efficient solutions by reducing the fleet size. Numerical results demonstrate that the proposed model has the potential to be applied for large-scale real-world networks.
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ISSN:2324-9935
2324-9943
DOI:10.1080/23249935.2017.1353555