Author:
Longo Giovanni,Montrone Teresa,Poloni Carlo
Publisher
Springer International Publishing
Reference32 articles.
1. Albrecht T, Oettich S (2002) Computers in Railways VII, chapter a new integrated approach to dynamic schedule synchronization and energy saving train control. WIT Press, Southampton, pp 847–856
2. Brunger O, Dahlhaus E (2009) Railway timetable and traffic: analysis, modelling and simulation, chapter running time estimation (4). Hamburg, Germany, pp 58–82
3. Chevrier R, Pellegrini P, Rodriguez J (2013) Energy saving in railway timetabling: a bi-objective evolutionary approach for computing alternative running times. Transp Res Part C 37:20–41
4. Cucala AP, Fernández A, Sicre C, Dominguez M (2012) Fuzzy optimal schedule of high speed train operation to minimize energy consumption with uncertain delays and driver’s behavioral response. Engineering Applications of Artificial Intelligence 25(8):1548–1557
5. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197