突发事件条件下铁路行车组织模糊随机优化方法
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摘要
摘要：目前,中国铁路基础设施建设正快速发展,其路网拓扑结构和运营管理模式正在发生深刻的变化,而我国现有的行车组织还是以运行区段为单位进行调度指挥的模式,基于路网的列车运行调度指挥既没有形成理论体系,也缺少相应的研究方法,严重影响整个运输系统的效率；同时,中国铁路自然灾害频发,铁路事故与铁路公共安全事件偶有发生,高速铁路和客运专线作为旅客运输的主要通道若发生能力损失,将对整个运输系统造成影响；此外,突发事件条件下的行车组织涉及对象多样、关系复杂,很容易受各类不确定性因素的影响,使得运营管理工作更加困难；因此,形成适合国情的突发事件条件下行车组织相关理论、方法及策略,是当前中国高速铁路快速发展背景下亟需解决的关键问题。
本文首先定义了不同类型突发事件条件下行车组织的科学问题,分析了不同类型行车组织原则、策略及流程,而后主要针对严重突发事件条件下行车组织展开研究,将其归结为一个突发事件触发的包含双层规划的多阶段闭环模糊随机优化过程。
深入分析突发事件条件下区间通过能力计算涉及的不确定因素,建立了基于模糊马尔科夫链的计算方法,提出了一种以模糊随机变量表达区间通过能力的解析形式。综合考虑突发事件条件下列车运行速度、线路能力、线路长度等因素,提出了线路能力相关的一种测度——线路能力时间强度和密度,并以此为基础实现了迂回径路搜索算法,使得迂回径路集更符合实际运营环境。
建立了突发事件条件下的开行方案和运行计划调整双层规划模型,上层对列车迂回、列车重联、列车停运等调度策略进行优化,以充分利用路网能力,完成旅客输送过程。在给定上层调度策略后,下层规划采取改变列车区间运行时间、列车停站时间和列车越行方式等策略,以尽量减少列车晚点,恢复按图运行,并为上层提供调整后的运行时刻表,实现双层迭代整体优化。随后对模型中涉及的不确定因素进行分析,并根据决策者的不同偏好建立期望值-容差模型和机会-容差模型。针对突发事件条件下开行方案与运行计划调整双层规划问题的特点,设计了嵌入分枝定界法的多方向植物生长模拟算法,给出了详细的计算步骤,同时确保行车组织原则的实施。
文章最后以京沪高速及相关铁路为背景进行实例分析。在分别证明开行方案和运行计划调整双层规划和不确定环境下容差模型有效性的基础上进行综合实验,实现了突发事件条件下的能力计算、迂回径路集搜索、限速条件下的运行计划调整、断路条件下的双层优化以及列车返回原径路的全过程。面向不同决策偏好的调整方案验证了本文所提出的突发事件条件下行车组织相关理论及方法。
ABSTRACT:The infrastructure of high-speed railway is extensively developed in China for the past several years. The network topology structure and operation mode of the railway are changing profoundly. The pattern of train operation in China is the one which takes the sections as the dispatching units. The theory system on network based dispatching has not been formed and the corresponding methods are rare, which seriously affects the capacity of the whole transport system. Railway natural disasters occur frequently, and there are occasional railway accidents railway safety public incidents in China. Capacity loss of high-speed railway that assumes the primary responsibility for passenger transport will affect the whole transport system. Furthermore, train operation in emergency involves diverse objects, complex relations and various uncertainties. It makes the railway management more difficultly. Thus, it is a key issue to achieve the train operation theory, method and strategy in emergency under the background of the rapid development of Chinese high-speed railway.
In this paper, we define the scientific issue of train operation optimization in different emergency, and analyze the principles, strategies and processes in different emergency. Then, our research focus on the problem of Train Operation in Serious Emergency and attribute it to an emergency triggered, bi-level programming and fuzzy and random parameters included, multi-stage, closed-loop optimization process.
We analyze the uncertain parameters of section capacity in emegency and establish the capacity calculation method based on fuzzy Markov chain. Then, the section capacity in emergency is expressed by fuzzy random variable. Considering train speed, line capacity, line length and other factors in emergency, we present a measure of capacity-related——Time Strength of Line Capacity and Time Density of Line Capacity. Rerouting path search algorithm is proposed based on the time reliability, and it obtains the rerouting path set which adapts to the actual operating environment.
In additional, we propose a bi-level programming to handle line plan adjustment and timetable rescheduling problem in emergency. The top layer objective is to make an optimal dispatching plan with selected actions which including merging trains, cancelling trains and making detour to other railway lines. This will take advantage of network capabilities to complete the passenger transport. Given a specific dispatching plan, the second layer (timetable rescheduling) of the optimization model focuses on minimizing the total delay as well as the number of seriously impacted trains by taking the strategies of changing the running time at a section, the dwell time at a station and the train stopovers. Then we analyze the uncertain factors of the model and put forward to expectation-tolerance model and chance-tolerance model according to the preferences of decision makers. It is solved by Branch and Bound Method mixed Multi-direction Plant Growth Simulation Algorithm (DPGSA). This ensures the implementation of the principle of train operation.
At last, we complete the cases studies of Beijing-Shanghai high speed railway. Based on the validity of bilevel programming and tolerance model, we realize the whole process of capacity evaluation in emergency, rerouting path searching, timetable adjustment with speed restriction, bi-level optimization with line interrupted and train return. The different optimal schemes, according to the preferences of decision makers, prove the theory and method of Train Operation in Emergency in this paper.
本文首先定义了不同类型突发事件条件下行车组织的科学问题,分析了不同类型行车组织原则、策略及流程,而后主要针对严重突发事件条件下行车组织展开研究,将其归结为一个突发事件触发的包含双层规划的多阶段闭环模糊随机优化过程。
深入分析突发事件条件下区间通过能力计算涉及的不确定因素,建立了基于模糊马尔科夫链的计算方法,提出了一种以模糊随机变量表达区间通过能力的解析形式。综合考虑突发事件条件下列车运行速度、线路能力、线路长度等因素,提出了线路能力相关的一种测度——线路能力时间强度和密度,并以此为基础实现了迂回径路搜索算法,使得迂回径路集更符合实际运营环境。
建立了突发事件条件下的开行方案和运行计划调整双层规划模型,上层对列车迂回、列车重联、列车停运等调度策略进行优化,以充分利用路网能力,完成旅客输送过程。在给定上层调度策略后,下层规划采取改变列车区间运行时间、列车停站时间和列车越行方式等策略,以尽量减少列车晚点,恢复按图运行,并为上层提供调整后的运行时刻表,实现双层迭代整体优化。随后对模型中涉及的不确定因素进行分析,并根据决策者的不同偏好建立期望值-容差模型和机会-容差模型。针对突发事件条件下开行方案与运行计划调整双层规划问题的特点,设计了嵌入分枝定界法的多方向植物生长模拟算法,给出了详细的计算步骤,同时确保行车组织原则的实施。
文章最后以京沪高速及相关铁路为背景进行实例分析。在分别证明开行方案和运行计划调整双层规划和不确定环境下容差模型有效性的基础上进行综合实验,实现了突发事件条件下的能力计算、迂回径路集搜索、限速条件下的运行计划调整、断路条件下的双层优化以及列车返回原径路的全过程。面向不同决策偏好的调整方案验证了本文所提出的突发事件条件下行车组织相关理论及方法。
ABSTRACT:The infrastructure of high-speed railway is extensively developed in China for the past several years. The network topology structure and operation mode of the railway are changing profoundly. The pattern of train operation in China is the one which takes the sections as the dispatching units. The theory system on network based dispatching has not been formed and the corresponding methods are rare, which seriously affects the capacity of the whole transport system. Railway natural disasters occur frequently, and there are occasional railway accidents railway safety public incidents in China. Capacity loss of high-speed railway that assumes the primary responsibility for passenger transport will affect the whole transport system. Furthermore, train operation in emergency involves diverse objects, complex relations and various uncertainties. It makes the railway management more difficultly. Thus, it is a key issue to achieve the train operation theory, method and strategy in emergency under the background of the rapid development of Chinese high-speed railway.
In this paper, we define the scientific issue of train operation optimization in different emergency, and analyze the principles, strategies and processes in different emergency. Then, our research focus on the problem of Train Operation in Serious Emergency and attribute it to an emergency triggered, bi-level programming and fuzzy and random parameters included, multi-stage, closed-loop optimization process.
We analyze the uncertain parameters of section capacity in emegency and establish the capacity calculation method based on fuzzy Markov chain. Then, the section capacity in emergency is expressed by fuzzy random variable. Considering train speed, line capacity, line length and other factors in emergency, we present a measure of capacity-related——Time Strength of Line Capacity and Time Density of Line Capacity. Rerouting path search algorithm is proposed based on the time reliability, and it obtains the rerouting path set which adapts to the actual operating environment.
In additional, we propose a bi-level programming to handle line plan adjustment and timetable rescheduling problem in emergency. The top layer objective is to make an optimal dispatching plan with selected actions which including merging trains, cancelling trains and making detour to other railway lines. This will take advantage of network capabilities to complete the passenger transport. Given a specific dispatching plan, the second layer (timetable rescheduling) of the optimization model focuses on minimizing the total delay as well as the number of seriously impacted trains by taking the strategies of changing the running time at a section, the dwell time at a station and the train stopovers. Then we analyze the uncertain factors of the model and put forward to expectation-tolerance model and chance-tolerance model according to the preferences of decision makers. It is solved by Branch and Bound Method mixed Multi-direction Plant Growth Simulation Algorithm (DPGSA). This ensures the implementation of the principle of train operation.
At last, we complete the cases studies of Beijing-Shanghai high speed railway. Based on the validity of bilevel programming and tolerance model, we realize the whole process of capacity evaluation in emergency, rerouting path searching, timetable adjustment with speed restriction, bi-level optimization with line interrupted and train return. The different optimal schemes, according to the preferences of decision makers, prove the theory and method of Train Operation in Emergency in this paper.
引文
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