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First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction

Xuan Li (), Toshiyuki Yamamoto (), Tao Yan (), Lili Lu () and Xiaofei Ye ()
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Xuan Li: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Toshiyuki Yamamoto: Institute of Materials and Systems for Sustainability, Nagoya University, Nagoya 464-8603, Japan
Tao Yan: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Lili Lu: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Xiaofei Ye: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China

Sustainability, 2020, vol. 12, issue 10, 1-22

Abstract: This paper proposes a novel model to optimize the first train timetables for urban rail transit networks, with the goal of maximizing passengers’ transfer waiting time satisfaction. To build up the relationship of transfer waiting time and passenger satisfaction, a reference-based piecewise function is formulated with the consideration of passengers’ expectations, tolerances and dissatisfaction on “just miss”. In order to determine the parameters of zero waiting satisfaction rating, the most comfortable waiting time, and the maximum tolerable waiting time in time satisfaction function, a stated preference survey is conducted in rail transit transfer stations in Shanghai. An artificial bee colony algorithm is developed to solve the timetabling model. Through a real-world case study on Shanghai’s urban rail transit network and comparison with the results of minimizing the total transfer time, we demonstrate that our approach performs better in decreasing extremely long wait and “just miss” events and increasing the number of passengers with a relatively comfortable waiting time in [31s, 5min). Finally, four practical suggestions are proposed for urban rail transit network operations.

Keywords: urban rail transit network; first train timetabling; passenger satisfaction; transfer; artificial bee colony algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2020
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