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静态配流是铁路编组站阶段计划的核心,模型和算法的优劣直接影响编组站作业效率和经济效益。本文基于约束程序累积调度和字典序多目标优化理论,考虑配流成功的出发列车优先级总和最大、出发车流来源总数最小、到达车辆先到先发等具有字典序的3个目标,以满轴、正点、不违编、解编顺序及编组场容量限制等为约束条件,建立静态配流字典序多目标累积调度模型。采用迭代、约束传播和回溯算法求解。通过现场实际数据验证:本算法求解时间满足现场要求;模型稳定、扩展性好,符合实际需求。
Static distribution is the core of the planning phase of railway marshalling station. The merits of the models and algorithms have a direct impact on the operation efficiency and economic benefits of marshalling station. In this paper, based on the constrained program cumulative scheduling and dictionary order multi-objective optimization theory, considering the priority of the successful distribution of the total train priority, the minimum total number of starting traffic flow, arrive at the vehicle first to start with the dictionary of three goals, Punctuality, non-defaulting, unordered sequence, and confined field capacity constraints, a multi-objective cumulative scheduling model of static allocation dictionary is established. Iteration, constraint propagation and backtracking algorithm. Validated by the actual field data: The algorithm solves the time to meet the requirements of the site; the model is stable, scalable, in line with the actual needs.