基于CCLPSO算法的Y型交路列车开行方案优化研究  

Optimization research of train schedule of Y-type train routing mode based on CCLPSO algorithm

作　　者：谭丽 韦子文 TAN Li;WEI Ziwen(School of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学自动化与电气工程学院

出　　处：《铁道科学与工程学报》2019年第8期2122-2129,共8页Journal of Railway Science and Engineering

基　　金：甘肃省教育厅自然科学基金资助项目(2017A-020);中国铁路总公司科技研究开发计划项目(2017J012-A)

摘　　要：列车开行方案通常包括列车停站方案、交路计划以及编组方案,是地铁组织运输的基础。结合交通运输组织的实践经验以及输送能力与客流需求达到最佳匹配的原则,以乘客出行成本及企业运营成本最低为目标,综合考虑线路最大通过能力、最小发车频率和最大可用车底数量等限制条件,构建城市地铁Y型交路模式下的列车开行方案优化模型,来确定Y型交路模式列车开行方案的主线及支线的列车运行区段及各线的列车开行频率。采用分类学习混合粒子群算法(CCLPSO)对其进行求解,通过实际案例验证了模型的合理性和算法的有效性,并对折返站位置和列车开行频率进行灵敏度分析。研究结果表明:Y型交路的折返站的选取对乘客出行成本影响显著,相比于其他2种算法,采用该算法可使综合成本分别减少16.9%和31.6%。The train schedule usually includes train stop schedule plan,routing scheme and formation scheme.It is the basis of subway transportation.Combining the practical experience of transport organizations and the principle of the best match between transport capacity and passenger flow demand,taking the minimum value of passenger travel costs and corporate operating costs as the goals,considering the constraints of maximum rail capacity,minimum departure frequency and maximum available electric multiple units,a optimization model for city subway Y-type operation mode is constructed to determine the operation section of mainline and branch line and the train frequency on both lines in the Y-type operation mode.The commix classified learning particle swarm algorithm (CCLPSO) was used to solve the model.The rationality of the model and the effectiveness of the algorithm were verified by a practical case,and the sensitivity analysis of the turn-back station and frequency were conducted.The results show that the selection of turn-back station affects the cost of waiting time of passengers significantly,the comprehensive cost can be reduced by 16.9% and 31.6% by comparing with the other two algorithms,respectively.

关 键 词：城市轨道交通 列车开行方案 混合粒子群算法 分类学习 

分 类 号：U2-9[交通运输工程—道路与铁道工程] TP312[自动化与计算机技术—计算机软件与理论]