基于免疫粒子群算法的闭塞分区划分优化设计  

Optimization Design of the Partitioning of Railway Block Section Based on Immune Particle Swarm Algorithm

作　　者：康宁[1] 陈永刚[1] 林俊亭[1] 曹岩[2] 

机构地区：[1]兰州交通大学自动化与电气工程学院,兰州730070 [2]兰州交通大学电子与信息工程学院,兰州730070

出　　处：《铁道标准设计》2013年第11期101-104,共4页Railway Standard Design

基　　金：国家自然科学基金资助项目(61074139);国家支撑计划项目(2009BAG11B02)

摘　　要：闭塞分区的划分优化能提高铁路通过能力,保证行车安全,因此对此问题进行研究是很有必要的。由于闭塞分区划分是多目标复杂非线性问题,在"经济"和"效率"下建立信号机布置的2种不同优化模型,并使用免疫粒子群算法对模型求解,通过列车追踪间隔检验、列车起动检验、列车停车检验,并对具体一条线路实现区间信号机布置。模拟实验结果表明,基于免疫粒子群算法的闭塞分区划分优化模型较之普通优化模型具有更高的有效性和鲁棒性。It is necessary to study the issue of the block section＇s partitioning so as to improve the carrying capacity of railway, and ensure traffic safety. Considering the partitioning of block section is a nonlinear problem with multi-objective complexity, the paper built two different optimization models of signaling layout in relation to＂ economy＂ and＂ efficiency＂, and adopted the immune particle swarm algorithm to solve the models. Moreover, a case study of signaling layout design for a certain railway line was conducted, with train headway test, train starting and stopping test. The results of simulation experiment demonstrate that the optimization model of block section＇s partitioning based on the immune particle swarm algorithm has stronger effectiveness and robustness in comparison with ordinary optimization models.

关 键 词：铁路信号 列车追踪间隔 免疫粒子群算法 闭塞分区 

分 类 号：U284.95[交通运输工程—交通信息工程及控制]