Non-dominated Sorting Bees Algorithm for Multi-Objective Train Speed Profile Optimization

Considering various factors like energy consumption and travel time, speed profile optimization is regarded as a non-linear, complex multi-objective problem. In this paper, a novel approach based on the Bees algorithm (BA) is proposed to solve train speed profile optimization. In this approach, BA is modified as a non-dominated sorting BA (NSBA) which produces a population that conducts a semi-stochastic search algorithm to determine critical points for acceleration changes forming a raw template as a trajectory. Afterward by local optimizations, the trajectory is amended to meet ending requirements. The simulation results indicate on effectiveness and excellence of the proposed method.