A Multi-Objective Robust Optimization Model for Customized Bus Routes

Abstract

Various customized bus route optimization methods based on certain conditions have been applied to the actual route optimization problems, but the actual operation process of customized buses mostly lies in an uncertain condition. In this paper, a three-stage hybrid coding method based on NSGA-II algorithm was proposed to deal with customized bus route optimization under uncertain condition. Firstly, with the objective of minimizing passenger travel time and customized bus carbon emission, a robust optimization model was constructed. Second, with the Bertsimas-Sim robust optimization theory, the robust peer-to-peer transformation was performed on the robust model with uncertain parameters. Finally, the practical issue including three customized bus parking lots and 20 boarding and alighting stations were solved to verify the rationality of the model and algorithm. Compared with the hybrid algorithm based on K-means and multi-objective genetic algorithm, this method reveals not only better solution results, but saves 42.11% of computing time. The results are of great value for exploring customized bus route optimization methods and improving the efficiency of customized bus operations.