Simulation based optimization of a train maintenance facility
Abstract
In this paper, a simulation based optimization method is developed for optimization of scheduling policies. This method uses the technique of coupling industrial simulation software with a multi-objective optimizer based on genetic algorithms. It is used to optimize the performances of a railway maintenance facility by choosing the best scheduling policy. Numerical results show that a significant improvement is achieved with respect to the simulation results of the existing system. The method adapted by our problem can be extended to deal with the selection of scheduling rules in using other types of simulation models.