Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control
The real-time traffic control has an important impact on the efficiency of the energy utilization in the modern railway network. This study is aimed to develop an energy-efficient railway traffic control solution for any specified railway. In other words, it is expected to define suitable driving pr...
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doaj-d233498b7ef34a009eb8bb1ef15bd8c52020-11-24T22:26:50ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/805410805410Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic ControlDaniel Tuyttens0Hongying Fei1Mohand Mezmaz2Jad Jalwan3Department of Mathematics and Operational Research, University of Mons, 9 Rue de Houdain, B7000 Mons, BelgiumSchool of Management, Shanghai University, No. 99 Shangda Road, Shanghai 200444, ChinaDepartment of Mathematics and Operational Research, University of Mons, 9 Rue de Houdain, B7000 Mons, BelgiumDepartment of Mathematics and Operational Research, University of Mons, 9 Rue de Houdain, B7000 Mons, BelgiumThe real-time traffic control has an important impact on the efficiency of the energy utilization in the modern railway network. This study is aimed to develop an energy-efficient railway traffic control solution for any specified railway. In other words, it is expected to define suitable driving profiles for all the trains running within a specified period through the targeted network with an objective to minimize their total energy consumption. How to optimize the train synchronization so as to benefit from the energy regenerated by electronic braking is also considered in this study. A method based on genetic algorithm and empirical single train driving strategies is developed for this objective. Six monomode strategies and one multimode strategy are tested and compared with the four scenarios extracted from the Belgian railway system. The results obtained by simulation show that the multi-mode control strategy overcomes the mono-mode control strategies with regard to global energy consumption, while there is no firm relation between the utilization rate of energy regenerated by dynamic braking operations and the reduction of total energy consumption.http://dx.doi.org/10.1155/2013/805410 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Daniel Tuyttens Hongying Fei Mohand Mezmaz Jad Jalwan |
spellingShingle |
Daniel Tuyttens Hongying Fei Mohand Mezmaz Jad Jalwan Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control Mathematical Problems in Engineering |
author_facet |
Daniel Tuyttens Hongying Fei Mohand Mezmaz Jad Jalwan |
author_sort |
Daniel Tuyttens |
title |
Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control |
title_short |
Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control |
title_full |
Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control |
title_fullStr |
Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control |
title_full_unstemmed |
Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control |
title_sort |
simulation-based genetic algorithm towards an energy-efficient railway traffic control |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2013-01-01 |
description |
The real-time traffic control has an important impact on the efficiency of the energy utilization in the modern railway network. This study is aimed to develop an energy-efficient railway traffic control solution for any specified railway. In other words, it is expected to define suitable driving profiles for all the trains running within a specified period through the targeted network with an objective to minimize their total energy consumption. How to optimize the train synchronization so as to benefit from the energy regenerated by electronic braking is also considered in this study. A method based on genetic algorithm and empirical single train driving strategies is developed for this objective. Six monomode strategies and one multimode strategy are tested and compared with the four scenarios extracted from the Belgian railway system. The results obtained by simulation show that the multi-mode control strategy overcomes the mono-mode control strategies with regard to global energy consumption, while there is no firm relation between the utilization rate of energy regenerated by dynamic braking operations and the reduction of total energy consumption. |
url |
http://dx.doi.org/10.1155/2013/805410 |
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