T. Albrecht, Railway Timetable & Traffic ? Analysis, Modelling, Simulation, chapter Energy-Efficient Operation Train Operation, pp.83-105, 2008.

T. Albrecht and S. Oettich, Computers in Railways VIII, chapter A new integrated approach to dynamic schedule synchronization and energy saving train control, pp.847-856, 2002.

O. Brünger and E. Dahlhaus, Railway Timetable & Traffic ? Analysis, Modelling, Simulation, chapter Running Time Estimation, pp.58-82, 2008.

C. S. Chang, D. Y. Xu, and H. B. Quek, Pareto-optimal set based multiobjective tuning of fuzzy automatic train operation for mass transit system, IEE Proceedings?Electric Power Applications, pp.577-583, 1999.
DOI : 10.1049/ip-epa:19990481

R. Chevrier, An evolutionary multi-objective approach for speed tuning optimization with energy saving in railway management, 13th International IEEE Conference on Intelligent Transportation Systems, pp.279-284, 2010.
DOI : 10.1109/ITSC.2010.5625026

URL : https://hal.archives-ouvertes.fr/hal-00465116

K. Deb, Multi-objective Optimization using Evolutionary Algorithms, 2001.

K. Deb and R. B. Agrawal, Simulated binary crossover for continuous search space, 1995.

K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan, A fast elitist nondominated sorting genetic algorithm for multi-objective optimization: Nsga-ii, Parallel Problem Solving from Nature PPSN VI, pp.849-858, 1917.

P. J. Fleming and R. C. Purshouse, Evolutionary algorithms in control systems engineering: a survey, Control Engineering Practice, vol.10, issue.11, 2002.
DOI : 10.1016/S0967-0661(02)00081-3

N. Hansen and A. Ostermeier, Completely Derandomized Self-Adaptation in Evolution Strategies, Evolutionary Computation, vol.9, issue.2, pp.159-195, 2001.
DOI : 10.1016/0004-3702(95)00124-7

C. Igel, N. Hansen, and S. Roth, Covariance Matrix Adaptation for Multi-objective Optimization, Evolutionary Computation, vol.15, issue.1, pp.1-28, 2007.
DOI : 10.1109/TEVC.2003.810758

Y. Jin and J. Branke, Evolutionary Optimization in Uncertain Environments???A Survey, IEEE Transactions on Evolutionary Computation, vol.9, issue.3, pp.303-317, 2005.
DOI : 10.1109/TEVC.2005.846356

D. Lancien and M. Fontaine, Calculs de marches de trainéconomisanttrain´trainéconomisant l'´ energie de traction ? le programme MARECO. Revue Générale des Chemins de Fer, pp.679-692, 1981.

A. Liefooghe, L. Jourdan, and E. Talbi, A unified model for evolutionary multiobjective optimization and its implementation in a general purpose software framework: ParadisEO-MOEO, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00376770

R. Liu and I. Golovitcher, Energy-efficient train control, Transportation Research part(A), vol.37, pp.917-932, 2003.

P. Lukaszewicz, Running resistance - results and analysis of full-scale tests with passenger and freight trains in Sweden, Proc. IMechE, Part F, pp.221-2183, 2007.
DOI : 10.1243/0954409JRRT89

R. Storn and K. Price, Differential evolution ? a simple and efficient heuristic for global optimization over continuous spaces, Journal of Global Optimization, issue.11, pp.341-359, 1997.

T. El-ghazali, Metaheuristics: from design to implementation, 2009.

E. Zitzler, M. Laumanns, and L. Thiele, SPEA2: Improving the strength pareto evolutionary algorithm, Swiss Federal Institute of Technology (ETH), 2001.

E. Zitzler and S. Künzli, Indicator-Based Selection in Multiobjective Search, Parallel Problem Solving from Nature -PPSN VIII, pp.832-842, 2004.
DOI : 10.1007/978-3-540-30217-9_84