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An optimisation method for train scheduling with minimum energy consumption and travel time in metro rail systems

An optimisation method for train scheduling with minimum energy consumption and travel time in... Both energy consumption and travel time are important indices to evaluate the efficiency of operations of metro rail systems. This paper proposes an optimisation method to schedule trains for reducing the energy consumption and travel time. Firstly, we formulate an integer programming model with timetable and speed control. Secondly, we design an optimal train control algorithm and an adaptive genetic algorithm to find a good solution. Finally, we conduct numerical examples based on the real-life operation data from the Beijing Yizhuang metro rail line of China. The results illustrate that the proposed approach can reduce energy consumption by 7.31% and reduce travel time by 3.26% in comparison with the current operation strategy. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transportmetrica B: Transport Dynamics Taylor & Francis

An optimisation method for train scheduling with minimum energy consumption and travel time in metro rail systems

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References (38)

Publisher
Taylor & Francis
Copyright
© 2015 Hong Kong Society for Transportation Studies Limited
ISSN
2168-0582
eISSN
2168-0566
DOI
10.1080/21680566.2015.1007577
Publisher site
See Article on Publisher Site

Abstract

Both energy consumption and travel time are important indices to evaluate the efficiency of operations of metro rail systems. This paper proposes an optimisation method to schedule trains for reducing the energy consumption and travel time. Firstly, we formulate an integer programming model with timetable and speed control. Secondly, we design an optimal train control algorithm and an adaptive genetic algorithm to find a good solution. Finally, we conduct numerical examples based on the real-life operation data from the Beijing Yizhuang metro rail line of China. The results illustrate that the proposed approach can reduce energy consumption by 7.31% and reduce travel time by 3.26% in comparison with the current operation strategy.

Journal

Transportmetrica B: Transport DynamicsTaylor & Francis

Published: May 4, 2015

Keywords: metro rail systems; energy consumption; travel time; adaptive genetic algorithm; operation strategy

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