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考虑节能目标的有轨电车时刻表优化
引用本文:张桐,毛保华,许奇,冯佳,唐继孟.考虑节能目标的有轨电车时刻表优化[J].交通运输工程学报,2019,19(6):171-181.
作者姓名:张桐  毛保华  许奇  冯佳  唐继孟
作者单位:1.北京交通大学 城市交通复杂系统理论与技术教育部重点实验室, 北京 1000442.北京交通大学 综合交通运输大数据应用技术交通运输行业重点实验室, 北京 1000443.湖南工业大学 交通工程学院, 湖南 株洲 412007
基金项目:国家自然科学基金项目71621001国家自然科学基金项目71571016
摘    要:研究了半独立路权下有轨电车时刻表的优化问题, 基于运行区间速度限制及区间首、末端节点构成, 对有轨电车运行区间进行了分类; 考虑有轨电车区间运行过程的复杂性, 构建了以减小列车总旅行时间和总能耗为目标的有轨电车区间车速引导节能优化模型; 为了使2个优化目标拥有相同的趋优满意程度, 提出了采用模糊数学规划的方法将双目标优化问题转化为单目标优化问题; 针对节能优化模型非线性特点, 设计了基于仿真的遗传算法对优化模型进行求解; 为了验证模型的有效性, 以南京市麒麟有轨电车1号线实际数据为基础, 选取某工作日早高峰7:00~8:00作为研究时段, 采用设计优化方法对既有时刻表进行了优化; 考虑企业管理者运营服务理念侧重性对优化结果的影响, 分别以最小旅行时间、最小能耗为目标的方案与本文模型对比。优化结果表明: 采用节能优化模型综合优化后的时刻表与既有运营时刻表相比, 其上行方向总旅行时间节省了124.9 s, 减少约7.7%, 下行方向总旅行时间节省了394.9 s, 减少约24.3%, 有效提升了有轨电车运行效率; 节能优化模型与最小旅行时间方案相比, 有轨电车上、下行总能耗分别降低了56.7%和53.5%, 与最小能耗方案相比, 上、下行有轨电车总旅行时间分别降低了14.9%和14.1%, 有效消解了旅行时间目标与能耗目标的冲突。 

关 键 词:城市轨道交通    有轨电车    时刻表优化    遗传算法    节能    区间车速引导
收稿时间:2019-07-02

Timetable optimization of tram considering energy saving goals
ZHANG Tong,MAO Bao-hua,XU Qi,FENG Jia,TANG Ji-meng.Timetable optimization of tram considering energy saving goals[J].Journal of Traffic and Transportation Engineering,2019,19(6):171-181.
Authors:ZHANG Tong  MAO Bao-hua  XU Qi  FENG Jia  TANG Ji-meng
Institution:1.MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China2.Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China3.School of Transportation Engineering, Hunan University of Technology, Zhuzhou 412007, Hunan, China
Abstract:The optimization problem of tram timetable in semi-exclusive right of way mode was studied, and the operation section was classified based on the speed limit and the composition of the head and end nodes. The complexity of tram section operation process was considered, and an energy saving optimization model of tram section speed guidance was constructed to reduce the total travel time and the total energy consumption. In order to make the two optimization objectives of total travel time and total energy consumption have the same degree of satisfaction, a fuzzy mathematical programming method was proposed to transform the double objective optimization problem into a single objective optimization problem. According to the nonlinear characteristics of the energy saving optimization model, a genetic algorithm based on simulation was proposed to solve the model. In order to test the validity of the model, based on the actual data of Qilin Tram Line 1 in Nanjing, the designed optimization method was used to optimize the existing timetable by selecting the 7:00-8:00 early peak period of a working day. Considering the influence of managers' operational service concepts on the optimization results, two schemes of minimum travel time objective and minimum energy consumption objective were designed and compared with the model. Optimization result shows that, compared with the existing operating timetable, the timetable adjusted by the energy saving optimization model saves 124.9 s in the upward direction, reducing by about 7.7%, and saves 394.9 s in the downward direction, reducing by about 24.3%. So, the optimization model can effectively improve the operation efficiency of the tram. Compared with the minimum travel time scheme, the total energy consumptions obtained by the optimization model in the upward and downward directions reduce by 56.7% and 53.5%, respectively. Compared with the minimum energy consumption scheme, the total train travel times obtained by the optimization model in the upward and downward directions reduce by 14.9% and 14.1%, respectively. So, the energy saving optimization model can effectively eliminate the conflict between travel time objective and energy consumption objective. 
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