高速磁浮车站列车作业优化与能力分析

邓连波; 陈晨; 静恩伟; 张颖; 霍亮

doi:10.19713/j.cnki.43-1423/u.T20222325

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高速磁浮车站列车作业优化与能力分析

高速铁路技术 | 更新时间：2023-12-05

- 高速磁浮车站列车作业优化与能力分析
- Train operation optimization and capability analysis of high-speed maglev station
- 铁道科学与工程学报 2023年20卷第11期页码：4041-4049
- 作者机构：
  
  1.中南大学交通运输工程学院湖南省轨道交通大数据实验室，湖南长沙 410075
  2.中铁第四勘察设计院集团有限公司线路站场设计研究院，湖北武汉 430063
- 作者简介：
  
  邓连波(1977—)，男，辽宁昌图人，教授，博士，从事交通运输规划与管理研究；E-mail：lbdeng@csu.edu.cn
- 基金信息：
  
  中国铁建股份有限公司2019年度科技重大专项(2019-A06);中铁第四勘察设计院集团有限公司科技研究开发计划项目(2019K110-1)
- DOI：10.19713/j.cnki.43-1423/u.T20222325
  中图分类号：
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邓连波,陈晨,静恩伟等.高速磁浮车站列车作业优化与能力分析[J].铁道科学与工程学报,2023,20(11):4041-4049.

DENG Lianbo,CHEN Chen,JING Enwei,et al.Train operation optimization and capability analysis of high-speed maglev station[J].Journal of Railway Science and Engineering,2023,20(11):4041-4049.
邓连波,陈晨,静恩伟等.高速磁浮车站列车作业优化与能力分析[J].铁道科学与工程学报,2023,20(11):4041-4049. DOI： 10.19713/j.cnki.43-1423/u.T20222325.

DENG Lianbo,CHEN Chen,JING Enwei,et al.Train operation optimization and capability analysis of high-speed maglev station[J].Journal of Railway Science and Engineering,2023,20(11):4041-4049. DOI： 10.19713/j.cnki.43-1423/u.T20222325.

摘要

高速磁浮作为一种高速度、高舒适性的便捷公共交通方式已成为公共交通的重要组成部分。目前高速磁浮方式整体上处于技术研发为主，商业运营仍处于起步阶段，特别是针对车站能力的研究较为缺乏。基于高速磁浮列车的运输组织要求，对高速磁浮车站的列车作业优化和能力利用问题进行研究。通过将高速磁浮车站到发线与径路一体化考虑，从车站径路运用和车站径路分段解锁的层面着手，在时间-空间双重约束下建立给定时刻表下高速磁浮车站作业安排优化模型。根据问题特性，将遗传算法的全局搜索性能和模拟退火算法的局部搜索性能相结合，设计遗传模拟退火算法。通过高速磁浮车站算例得出总延误为0的车站作业安排优化方案，并对车站能力利用状况进行分析。设计基于列车作业紧凑安排的车站能力启发式算法，通过压缩给定时刻表下车站接发车作业的间隔时间，计算特定的车流构成类型和比例下的高速磁浮车站通过能力。对比分析不同运行图场景下的高速磁浮车站通过能力，探索其一般规律。分析得出不停站通过列车、始发终到列车、停站通过列车、立折列车对车站通过能力利用效率依次降低的规律。该研究从列车车站列车作业组织角度丰富了高速磁浮技术，可为高速磁浮车站的作业安排和能力利用提供借鉴。

Abstract

High-speed maglev has grown to be a significant component of public transportation as a practical method offering high speed and great comfort. The high-speed maglev system is currently in the technology research and development phase, and its commercial operation is still in its infancy, especially not much research has been done on station capacity. The train operation optimization and capacity utilization of high-speed maglev stations were investigated based on the transportation organization needs of high-speed maglev trains. Considering the integration of arrival-departure tracks and routes of high-speed maglev station, an optimization model of high-speed maglev station operation arrangement based on the provided schedule was established under the dual constraints of time and space from the aspects of station route application and station route section unlocking. Based on the characteristics of the problem, a genetic simulated annealing algorithm was developed by combining the global search performance of the genetic algorithm with the local search performance of the simulated annealing method. A case was used to obtain the optimization scheme of station operation arrangement with total delay of 0, and the utilization of station capacity was examined. To calculate the carrying capacity of high-speed maglev stations under a specific type and proportion of train flow by compressing the interval time between station receiving and dispatching trains in a given schedule, a heuristic algorithm based on the compact arrangement of train operation was designed. Comparing, evaluating, and exploring the general principles of the station carrying capacity under various train diagram scenarios of transport demand. It is concluded that the utilization efficiency of station carrying capacity decreases successively by the through train without stop, arrival-departure train, through train with stop, turn-back train. This study completes high-speed maglev technology from the standpoint of train operation organization at the train station, which can provide reference for the operation arrangement and capacity utilization of high-speed maglev station.

关键词

高速磁浮作业安排车站能力遗传模拟退火算法

Keywords

high speed maglevassignment arrangementstation capacitygenetic simulated annealing algorithm

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