Journal
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
Volume 3, Issue 2, Pages 79-98Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/21680566.2015.1007577
Keywords
energy consumption; operation strategy; adaptive genetic algorithm; metro rail systems; travel time
Funding
- Beijing Laboratory of Urban Rail Transit
- Beijing Key Laboratory of Urban Rail Transit Automation and Control
- China Scholarship Council
- National Natural Science Foundation of China [71371027]
- Program for New Century Excellent Talents in University [NCET-13-0649]
- Fundamental Research Funds for the Central Universities [2014YJS022]
- Beijing Nova Program [Z14111000180000]
- State Key Laboratory of Rail Traffic Control and Safety [RCS2014K011, RCS2012ZQ003]
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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.
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