In railway planning, the timetabling step needs, as input, the train running times, which are calculated from a train dynamic model. Usually, this model determines the most energy-efficient train trajectory for a predefined time. However, this time may not correspond to the timetable-makers’ needs. They should have the choice among a set of solutions, more or less energy-consuming. This study proposes a method capable of producing a set of alternative running times with the associated mechanical energy required. To this end, the authors’ contribution is to set up an efficient evolutionary multi-objective algorithm builds a set of well-spread and diversified solutions which approximate a Pareto front. The solutions are all compromises between running time and energy-consumption, the two minimisation objectives concurrently optimised. Given that an evolutionary algorithm is strongly dependent on the initialisation phase, the efficiency of the algorithm is improved through a specific and original mechanism connecting multiple initialisations in cascade in order to accelerate the convergence towards the best solutions. A set of results obtained on randomly-generated instances is analysed and discussed.
Towards eco-aware timetabling: evolutionary approach and cascading initialisation strategy for the bi-objective optimisation of train running times
IET Intelligent Transport Systems ; 10 , 7 ; 483-494
2016-09-01
12 pages
Article (Journal)
Electronic Resource
English
Pareto front , Pareto optimisation , railways , evolutionary approach , biobjective optimisation , mechanical energy , initialisation phase , train dynamic model , train running times , timetable makers , ecoaware timetabling , railway planning , evolutionary computation , minimisation objectives , evolutionary algorithm , cascading initialisation strategy
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