Multiobjective trajectory optimization for electric trains

This paper develops a method for generating Pareto efficient trajectories that provide optimal tradeoffs between two conflicting attributes-the total energy consumed and the total time taken to complete each trajectory. Straightforward formulations of the multiobjective optimization problem in these attributes are difficult to solve because of certain nonlinearities in train models and certain constraints on train trajectories. A discrete reformulation is developed to circumvent these difficulties and produce computationally feasible algorithms. The results from the algorithms can be used to develop operating strategies for existing systems and to compare hardware alternatives in planning new systems. An illustration is included.