基于多目标遗传算法的地铁车辆回库股道安排

科学安排地铁车辆回库股道对提高车辆段生产效率具有重要意义，文章采用多目标遗传算法对回库股道安排进行优化。对车厂线路布置、车辆出入库方式进行分析并对回库股道安排问题进行描述，以任务完成度、接车过程总调车次数、车辆出入库额外耗时为优化目标，以车辆回库时间间隔、车辆段检修能力为约束建立基于多目标遗传算法的回库股道安排模型，以极限情况为例对算法性能进行测试，验证了模型的有效性。

Track arrangement in metro depot based on genetic multi-objective algorithm

The scientific arrangement of tracks has important significance to guarantee the work efficiency in metro depot. In this article, genetic multi-objective algorithm was applied to optimize the track arrangement for the metros to be returned. The article analyzed the track layout and the entrance/exit access, described the mathematical model of the problem, taken task completion degree, the total number of shunting times and extra time-consuming as the optimization targets, taken time interval and maintenance capability as the constraints, to set a track arrangement model based on genetic multi-objective optimization. Finally, the performance of the algorithm under the limited condition was tested and the effectiveness of model was validated.