考虑复杂场景的常导高速磁浮辅助停车区优化布置

Layout Optimization of Auxiliary Stopping Areas for Normal High-Speed Maglev Considering Complex Scenarios

摘要:

针对辅助停车区（ASA）布置的复杂场景，面向多目标速度曲线共存线路，以辅助停车区数量与列车区间追踪时间最小化为目标，以列车安全运行为约束，构建了多目标优化模型，设计与讨论了带精英策略的快速非支配排序遗传算法（NSGA-II），提出了一种考虑辅助停车区布置特征的种群初始化策略，使得算法具有良好计算性能。算例仿真验证了模型与算法解决复杂场景下辅助停车区优化布置的有效性，为求解辅助停车区布置问题提供了新思路。

Abstract:

For the layout of auxiliary stopping areas （ASAs） considering complex scenarios， taking the line with multi-target speed profiles as research objects， aimed at minimizing the number of ASAs and the train tracking interval， a multi-objective optimization model constrained with the safe operation of trains is established. In addition， a fast and elitist non-dominated sorting generic algorithm （NSGA-II） is designed and discussed. Moreover， to make the algorithm has a better performance， a population initialization strategy considering the layout characteristics of ASAs is proposed. The simulation results verify the effectiveness of the model and the algorithm on solving the layout problem of ASAs in complex scenarios. This paper can provide a new idea for solving related problems.