Energy Saving Train Operation Optimization with Adaptive Genetic Algorithm

In order to improve the train energy saving optimization strategy,the existing energy saving operation experiences and typical sub-interval thought were combined and the Adaptive Genetic Algorithm was introduced,to seek for the switching point and make the train operation energy consumption minimum,under different working conditions.Fire,the preconditions of safety,punctuality and comfortable were fulfilled,the train parking brake curve and the computing method of speed limit protection curve were introduced,and the train speed curve was fixed by prefabricating the train parking brake curve and the speed limit protection curve to achieve the purpose of enhancing the proportion of feasible genetic algorithm solution and accelerating the algorithm iterative process.Then,we explained the choice method of chromosomes and operator of genetic algorithm as well as the fitness function and iterative convergence conditions in detail.The application of adaptive mechanism strengthens the global searching capability of genetic algorithm.The line of Wuhan toXinwulongquan was taken as an example which shows that this energy saving optimization algorithm is of validity.