Energy saving in railway timetabling: A bi-objective evolutionary approach for computing alternative running times
Document Type
Journal Article
Publication Date
2013
Subject Area
mode - rail, place - europe, planning - environmental impact, operations - scheduling
Keywords
Running time, Energy saving, Railway timetabling, Multi-objective, Evolutionary algorithm, Optimization
Abstract
The timetabling step in railway planning is based on the estimation of the running times. Usually, they are estimated as the shortest running time increased of a short time supplement. Estimating the running time amounts to define the speed profile which indicates the speed that the train driver must hold at each position. The approach proposed in this paper produces a set of solutions optimizing both the running time and energy consumption. The approach is based on an original method of speed profiling performed by a multi-objective evolutionary algorithm. The speed profiles found by the evolutionary algorithm are all compromises between running time on the one hand and energy consumption on the other hand. A set of results obtained on two lines are analyzed and discussed to highlight the relevance of such an approach in a practical context.
Rights
Permission to publish the abstract has been given by Elsevier, copyright remains with them
Recommended Citation
Chevrier, R., Pellegrini, P., & Rogriguez, J. (2013). Energy saving in railway timetabling: A bi-objective evolutionary approach for computing alternative running times. Transportation Research Part C: Emerging Technologies Volume 37, December 2013, Pages 20–41.
Comments
The timetabling step in railway planning is based on the estimation of the running times. Usually, they are estimated as the shortest running time increased of a short time supplement. Estimating the running time amounts to define the speed profile which indicates the speed that the train driver must hold at each position. The approach proposed in this paper produces a set of solutions optimizing both the running time and energy consumption. The approach is based on an original method of speed profiling performed by a multi-objective evolutionary algorithm. The speed profiles found by the evolutionary algorithm are all compromises between running time on the one hand and energy consumption on the other hand. A set of results obtained on two lines are analyzed and discussed to highlight the relevance of such an approach in a practical context.