奥运通勤线路公交调度问题研究

奥运通勤线路上的人员调度问题可以归结为公交人员调度问题,解决公交人员调度通常采用"生成与选择"模式,此种模式具有的局限性使之不能满足解决奥运特色通勤线路上人员调度的要求.针对多条运营线路的奥运特色通勤线路人员调度问题,给出了奥运特色通勤线路人员调度问题的改进模型,模型的目标是在满足工作时间、就餐时间、换班要求等相关约束的条件下使人员完成任务的间隔时间最小.本文对已有蚁群算法解决车辆路径优化问题的算法进行了改进.对算法中相应的转移规则和轨迹更新规则进行了重新设定,改进了算法转移策略和信息素更新策略.给出了算法的实现步骤.通过仿真,对模型的正确性进行了验证.证明了改进蚁群算法解决奥运特色通勤线路人员调度问题的高效性和较强的适用性.

Modeling and Solving for Transit Scheduling Problem on Olympics Transport

Crew Scheduling Problem on Olympics Transport(CSPOT) belongs to the general class of transit crew scheduling problem(TCSP).Cluster First-Schedule Second(CFSS) is the common mode used in solving TCSP.CFSS has inherent limitations which makes it improper in dealing with CSPOT.An improved model was presented to model CSPOT,and the objective was to schedule crews in such a way that the deadheading was minimized while the operational constraints such as working duration,meal duration and shift condition were satisfied.Ant colony algorithm(ACA) was devised to solve CSPOT based on principle of ACA used to solve vehicle routing problem(VRP).Improvement on route construction rule and pheromone updating rule was adopted on the basis of former algorithm.An example was analyzed to demonstrate the correctness of the application of this algorithm.It is proved that ACA is efficient and robust in solving CSPOT.