基于最远站法则的列车编组计划优化双层规划模型

The Bi-Level Programming Model for Optimizing Train Formation Plan and Technical Station Load Distribution Based on the Remote Re-Classification Rule

根据铁路现场车流组织的实际特点,构建基于最远站法则的列车编组计划优化双层规划模型。上层规划模型以车流组织总成本最小为目标函数,以车流组织方案的唯一性、技术站的改编能力、调车线的数量等为约束条件,确定列车编组去向的开行方案。下层规划模型以车流改编距离最远为目标函数,以站点出入流量平衡为约束条件,按照最远站法则确定车流改编接续方案。采用模拟退火算法对双层规划模型进行求解,得到了符合最远站法则的列车编组计划优化方案。通过案例的计算结果验证了模型和算法的有效性。

According to the real features of railway car flow organization,this paper proposes the remote re-classification rule,constructs a bi-level programming model for optimizing train formation plan and technical station load distribution.The upper level based on the train formation plan and technical station load distribution,aims at minimizing the total cost of railway car flow organization,considers the uniqueness of car flow organization,the station＇s re-classification ability and the number of shunting line as constraints,generates the plan of direct-arrive trains.The lower level targets at the longest re-classification distance,with the balanced in and out car flow at the station as the constraint,follows the remote re-classification rule to form the plan of car flow re-classification and connection.Simulated annealing algorithm is utilized to solve the bi-level programming model to get the optimization scheme for train formation plan which accords with the remote re-classification rule,and finally a large-scale actual railway network case is solved to verify the effectiveness of the model and the algorithm.