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基于我国铁路网络规模大、列车组织形式多样化以及按图行车的特点,设计了与物理时空网络有所区别的服务时空网络.时空网是研究铁路动态车流组织的一种有效方法.借助于服务时空网,构建了我国铁路运输动态车流组织的策略优化模型,该模型将重空车运输联合考虑,并兼顾站点装卸能力、解编能力、输送能力以及政策性运输任务等对优化目标的影响.基于模型的特点,设计了能解决大规模网络问题的基于整数编码的改进遗传算法.最后以实例显示了该算法的有效性.
Based on the large scale of China’s railway network, the diversity of train organization and the characteristics of driving according to the map, the service space-time network is designed to be different from the physical space-time network.As an effective method to study the dynamic railway flow organization, Time network to build a strategic optimization model of dynamic railway flow organization in China. The model considers the transportation of heavy-duty trucks jointly and takes into account the impact of site loading and unloading capacity, disassembly capacity, transmission capacity and policy transportation tasks on the optimization objectives. Based on the characteristics of the model, an improved genetic algorithm based on integer coding is designed, which can solve large-scale network problems.Finally, an example is given to show the effectiveness of the algorithm.