基于资源可用度的综合自动化编组站集群调度耦合优化模型与算法

项目名称： 基于资源可用度的综合自动化编组站集群调度耦合优化模型与算法

项目编号： No.61203175

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 自动化学科

项目作者： 薛锋

作者单位： 西南交通大学

项目金额： 23万元

中文摘要： 在编组站综合自动化逐步推进的背景下，以编组站调度系统为研究对象，采用理论与仿真实验相结合的方法对集群资源特性及耦合机制进行分析和建模。通过总结编组站综合自动化的特点及作业流程变化，对编组站集群资源进行分析，提出融入有界随机变量的资源可用度，明确各作业间的耦合关系，阐明编组站实体资源的集群控制机制。建立综合自动化条件下基于资源可用度的编组站集群调度耦合优化模型，包括静态计划与动态车流之间的耦合、作业计划与本务机调度之间的耦合、作业计划与列车编组计划之间的耦合，三个方面从时间、空间、车流组织模式上层层推进。在前期算法研究的基础上，基于信息熵和混沌理论的遗传-蚁群协同优化算法提出求解上述模型的改进智能算法，并对模型的应用进行测试和校正。本课题将揭示编组站调度系统作业间的耦合关系以及它们之间的集群控制机制，为综合自动化编组站实现高度智能化调度奠定理论基础。

中文关键词： 编组站调度系统；集群资源；资源可用度；优化模型；智能算法

英文摘要： Regard dispatching system of marshalling station as the research object, cluster resource characteristics and coupling control mechanism were analyzed using the combination method of theory and simulation experiment, under the background of fact that the integrated automation of marshalling station advances progressively. The cluster resource availability of marshalling station including constrained random variables was proposed through summarizing the characteristics and operation procedure changes of integrated automation, the coupling relation among every operation was defined, and then the cluster control mechanism of entity resource was expounded. Coupling optimization models for cluster dispatching in marshalling station were constructed on the basis of resource availability under integrated automation, the models include coupling optimizations among static plan and dynamic wagon-flow, operation plan and leading locomotive dispatching, operation plan and train formation plan. They promote by gradually from three respects in time, space, wagon-flow organization mode. On the foundation of studying on the previous algorithm, the improved intelligent algorithm was put forward which solves the above-mentioned model by genetic and ant colony collaborative optimization algorithm based on information entropy and c

英文关键词： marshalling station dispatching system；cluster resource；resource availability；optimization model；intelligent algorithm