WEI Zi-wen
（China Railway First Survey and Design Institute Group Co., Ltd., Xi’an 710043， China）
Abstract： The train schedule usually includes train stop schedule, 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 corporation operating costs as the goal, considering the constraints of the maximum rail capacity, the minimum departure frequency and the maximum available electric multiple unit, an optimization model for city subway Y-type operation mode is constructed to determine the operation section of mainline as well as branch line and the train frequency of the Y-type operation mode. The particle swarm optimization (PSO) algorithm based on classification learning is used to solve the model, and the effectiveness of the model and algorithm is verified by a practical case. The results show that the length of branch line in Y-type operation affects the cost of waiting time of passengers significantly.
Key words： urban traffic; train schedule； particle swarm optimization (PSO)； classification learning； Y-type train routing
CLD number： TP312 doi： 10.3969/j.issn.1674-8042.2020.01.011
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城市轨道交通Y型交路列车开行方案粒子群优化设计
韦子文
（中铁第一勘察设计院集团有限公司， 陕西 西安 710043）
摘 要：列车开行方案通常包括列车停站方案、 交路计划及编组方案， 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， 构建了城市地铁Y型交路模式下的列车开行方案优化模型， 并确定了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。 采用基于分类学习的粒子群算法对其进行求解， 并通过算例验证模型和算法的有效性， 对折返站和各交路区段的列车开行频率进行各成本的灵敏度分析。 结果表明， Y型交路其支线的长度对乘客候车等待时间成本影响显著。
关键词： 城市交通； 列车开行方案； 粒子群算法； 分类学习； Y型交路
引用格式： WEI Zi-wen. Particle swarm optimization for train schedule of Y-type train routing in urban rail transit. Journal of Measurement Science and Instrumentation, 2020, 11（1）： 87-93. ［doi： 10.3969／j.issn.1674-8042.2020.01.011］
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