The continuous expansion of coal mining in the Central Queensland Region is requiring more rail services to transport coal from the mine to port. Rail services have been expanding to meet this need with more rail routes, duplication of rail lines, increased number of trains and longer trains. When the length of trains are increased there is a need to review that these longer trains can be driven satisfactorily on the current rail lines. The driving strategies of longer trains need to consider the increased mass and length of the trains to ensure the coupling forces within the trains are within reasonable levels. Driving strategies have to consider multiple parameters such as operating the train safely, efficiently in terms of energy, in a timely manner and with minimal wear and damage to coupling components. This paper presents the use of computer based methods to determine optimal driving strategies for long trains. A number of computer based methods already exist but tend to be based around energy efficiency methods. Energy efficiency methods fail to completely consider the longitudinal coupling forces that are generated within the train. Research at the Centre for Railway Engineering, CQUniversity is gradually investigating the use of a computer based searching method based on ‘Genetic Algorithms’ to determine optimal driving strategies for long trains considering energy, time and longitudinal forces. Initial results have shown energy optimisation is possible by using Genetic Algorithms and a similar method is being developed to optimise for both energy and in-train forces.