Heavy haul trains are a very efficient way to transport bulk material over land. One way to increase network capacity and reduce operating costs is to use longer and heavier trains. Worldwide, railway operators are increasing the length and weight of heavy haul trains. However, longer trains tend to exhibit larger steady state and dynamic longitudinal coupler forces. Large coupler forces can increase the probability of derailments, and cause increased wear and damage to coupling components. Driving strategies need to be determined to ensure that the train is operated efficiently, safely, without excessive wear and in a timely manner. Improved driving strategies can be created by using experienced drivers, field tests and simulator trials. Recently some computer based optimisations methods have been developed to also improve driving strategies. Computer based optimisation methods have the advantage that they can be used to more easily assess the effect of changing train configurations, track topography or speed restrictions. Current computer based optimisations are good at optimising energy and time but there is a lack of optimisation methods that also consider longitudinal train forces. Research conducted at the Centre for Railway Engineering is investigating the use of computational techniques such as genetic algorithms to determine driving strategies of long trains. This paper presents a review of current optimisation methods and the progress in using genetic algorithms.