基于列生成与NSGA-II的多目标电动公交车辆调度研究

With the increasingly serious problems of urban traffic congestion and environmental pollution, public transport priority and green vehicles travel using new energy vehicles has gradually become a new concept advocated by the government. Due to the characteristics of green environmental protection and low transportation cost, the application of electric vehicles in public transportation system is increasing day by day. In terms of operation planning, compared with traditional fuel vehiclesscheduling, electric vehicles scheduling increases the maximum mileage and charging factor. In the existing research, single objective optimization is mostly used. In this paper, the mixed integer programming model of electric bus scheduling problem is constructed, and a hybrid optimization method combining column generation and NSGA-II is proposed to solve the problem. The column generation algorithm is applied to solve the main problem and the subproblem to determine the search space, and then the NSGA-II is used to carry out the multi-objective optimization with the operation cost and train number non coverage rate as the objective function. The experimental results show that the Pareto solution obtained by the hybrid optimization method has the solution dominating the manual scheduling scheme, and the highest cost of the solution is 11.47%, which indicates that the hybrid optimization method can effectively solve the multi-objective electric vehicles scheduling problem.