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面向OD客流的高速列车开行方案的优化
引用本文:田慧欣,王帝,帅民伟,李坤.面向OD客流的高速列车开行方案的优化[J].东北大学学报(自然科学版),2020,41(11):1535-1542.
作者姓名:田慧欣  王帝  帅民伟  李坤
作者单位:(1. 天津工业大学 电气工程与自动化学院, 天津300387; 2.天津工业大学 电工电能新技术天津重点实验室, 天津300387; 3.天津工业大学 经济与管理学院, 天津300387)
基金项目:国家自然科学基金资助项目(71602143,51607122); 天津市自然科学基金资助项目(18JCYBJC22000); 天津市高等学校创新团队培养计划项目(TD13-5038).
摘    要:满足旅客出行需求的列车开行方案能够更好地吸引客流,提高高速铁路的核心竞争力.以最大化经济收益和最小化出行费用为目标函数,以高速铁路开行方案为研究对象,以旅客出行需求等作为约束条件,将列车开行方案与OD客流量结合起来,同时考虑旅客的购票心理和列车购票的时效性,建立了一种基于动态客流的列车开行方案的多目标优化模型,并设计一种基于个体信息和改进变异算子的多目标差分(SG-MOSaDE)算法进行求解.以广州市某线路为例进行实验,结果表明,优化后的开行方案不仅最大化满足了旅客出行需求,而且在提高铁路部门经济收益的同时降低了旅客的出行花费,并且优化后的列车总停站次数较原来有所下降,停站方案更加均衡.

关 键 词:高速列车  多目标优化  OD客流  开行方案  差分进化算法  
收稿时间:2019-09-17
修稿时间:2019-09-17

Optimization of High-Speed Train Operation Plan for OD Passenger Flow
TIAN Hui-xin,WANG Di,SHUAI Min-wei,LI Kun.Optimization of High-Speed Train Operation Plan for OD Passenger Flow[J].Journal of Northeastern University(Natural Science),2020,41(11):1535-1542.
Authors:TIAN Hui-xin  WANG Di  SHUAI Min-wei  LI Kun
Institution:1. School of Electrical Engineering and Automatic, Tiangong University, Tianjin 300387, China; 2.Tianjin Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tiangong University, Tianjin 300387, China; 3.School of Economics and Management, Tiangong University, Tianjin 300387, China.
Abstract:The train operation plan that meets the passenger travel needs can better attract passenger flow and improve the core competitiveness of high-speed railway. The maximization of economic benefits and the minimization of travel expenses as the research objects, the high-speed rail operation plan as the research object, and the travel demand of passengers as constraints are taken. The train operation plan is combined with the OD passenger flow. Taking into account the passengers’ purchase psychology and the timeliness of train ticket purchase, a multi-objective optimization model of train operation plan is established based on dynamic passenger flow. In order to solve the problem, a multi-objective differential (SG-MOSaDE) algorithm is designed based on individual information and the improved mutation operator. Taking a certain route in Guangzhou as an example, the results show that the optimized operation plan not only maximizes meeting the passenger travel demand, but also reduces the travel expenses of the passenger while improving the economic benefits of the railway sector. The number of stations has decreased compared with the original, and the stop plan is more balanced.
Keywords:high-speed train  multi-objective optimization  OD passenger flow  operation plan  differential evolution algorithm  
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