高速铁路网络能力计算研究

张嘉敏; 张嘉锐

高速铁路网络能力计算研究

张嘉敏¹,
张嘉锐²

1.
山东科技大学交通学院,青岛 266590;
2.
济南铁路局青岛机务段,青岛 266041

基金项目: 山东科技大学人才引进科研启动基金项目（2014RCJJ025）。

详细信息

作者简介:
张嘉敏，讲师；张嘉锐，工程师。

中图分类号: U238:U293:TP39
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- 文章访问数: 107
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出版历程
- 收稿日期: 2016-02-16
- 刊出日期: 2016-08-24

Calculation of network capacity for high-speed railway

ZHANG Jiamin¹,
ZHANG Jiarui²

1.
College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China;
2.
Qingdao Locomotive Depot, Jinan Railway Administration, Qingdao 266041, China

摘要

摘要: 充分考虑高速铁路网络作为多级递阶控制系统的复杂性和对旅客运输服务质量的要求，构建基于时段特定场景的高速铁路列车服务与需求意向集合（t@n-tsdis，train service-demand intention setat network），定义以完成这个集合所需基础设施占用时间为网络能力的衡量标准。提出了两阶段的优化计算方法，并提出多目标优化改进的Pareto（1+1）— PAES算法流程，采用交互式滚动优化策略处理整数约束条件、模糊逻辑罚函数法处理连续实数约束条件、Pareto存档进化策略求解多目标优化问题。以某高速铁路网络为例进行能力计算，验证了模型与算法的有效性。
- 高速铁路 /
- 网络能力 /
- 列车径路规划 /
- 多目标优化 /
- Pareto存档进化策略
Abstract: Taking full account of the high speed railway network as the complexity of the multilevel hierarchical control system and requirements for the quality of passenger transport service, this article set up the high-speed train service-demand intention set at railway network according to the specific scenario of the period ( train service-demand intention set at network, abbreviated as t@n-tsdis ), and then took the occupation time of the infrastructures needed to fulfill the set as the criteria to measure the network capacity, proposed the two stage optimization calculation method. On solving the model, the article proposed improved (1+1)-PAES Algorithm flow for multi-objective optimization, and took the interactive-rolling strategy to tackle the integer constraints, the fuzzy-logic penalty function to tackle the real constraints, and the Pareto archived evolution strategy to solving multi-objective optimization problems. The model and the Algorithm were applied to a high speed railway network for case study, the validity of the model and the Algorithm was verified.
- high-speed railway /
- network capacity /
- train path planning /
- multi-objective optimization /
- Pareto archived evolution strategy

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参考文献(6)

[1]	Landex, A. Methods to estimate railway capacity and passenger delay[D]. Denmark: Technical University of Denmark, 2008.
[2]	张嘉敏. 高速铁路能力计算与评估之理论与方法研究[D]. 北京：北京交通大学，2012.
[3]	Michiel J.C.M. Vromans. Reliability and heterogeneity of railway services[J]. European Journal of Operational Research, 2006: 647–665.
[4]	Tijs Huisman, Richard J.Boucherie. Running times on railway sections with heterogeneous train traffic[J]. Transportation Research Part B , 2001 (35): 271-292.
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[6]	Joshua D. Knowles, David W. Corne. Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy[J]. Evolutionary Computation， 1999，7(1):1-24.

施引文献(6)

期刊类型引用(3)

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2.	张嘉敏，张嘉锐. 轨道交通基于大数据智能运营策略与框架综述. 综合运输. 2019(11): 50-56 . 百度学术
3.	张嘉敏，张嘉锐. 成网条件下沪宁杭城际高铁公交化开行方案研究. 铁路计算机应用. 2018(02): 35-38 . 本站查看