山东科学 ›› 2024, Vol. 37 ›› Issue (4): 121-130.doi: 10.3976/j.issn.1002-4026.20230098

• 交通运输 • 上一篇    下一篇

高速铁路枢纽场站能力综合利用研究

张杰1(), 何世伟2,*(), 赵日鑫2, 陈旻瑜1, 刘杰1   

  1. 1.山东铁路投资控股集团有限公司 运营管理部,山东 济南 250014
    2.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 100044
  • 收稿日期:2023-06-12 出版日期:2024-08-20 发布日期:2024-08-05
  • 通信作者: 何世伟 E-mail:15866750097@163.com;shwhe@bjtu.edu.cn
  • 作者简介:张杰(1971—),男,高级工程师,研究方向为交通运输规划与管理。E-mail:15866750097@163.com
  • 基金资助:
    山东铁路投资控股集团有限公司科研项目(2022-SDRI-YY-0002)

Study on comprehensive utilization of high-speed railway hub stations

ZHANG Jie1(), HE Shiwei2,*(), ZHAO Rixin2, CHEN Minyu1, LIU Jie1   

  1. 1. Operation Management Department, Shandong Railway Investment Holding Group Co., Ltd., Jinan 250014, China
    2. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
  • Received:2023-06-12 Online:2024-08-20 Published:2024-08-05
  • Contact: HE Shiwei E-mail:15866750097@163.com;shwhe@bjtu.edu.cn

摘要:

为统筹利用高速铁路枢纽内的旅客运输资源,研究高速铁路枢纽内客运场站的分工问题。以枢纽内列车总作业时间最小和场站能力协调为优化目标构建多目标整数规划模型,通过设计增广ε-约束算法求解模型的近似非支配前沿。以郑州高速铁路枢纽为例展开实例分析,从定性和定量的角度分别对原有方案与优化方案的差异及能力适应性进行比较,验证模型及算法的可行性和有效性。结果表明,增广ε-约束算法可以为所提出模型寻找到高质量的代表性非支配解,所得出的优化方案能够降低枢纽内列车的作业时间,提高场站能力利用协调度,可为高铁枢纽地区扩能改造、能力优化等措施的决策提供可靠参考依据。

关键词: 铁路运输, 能力利用, 多目标优化, 高速铁路枢纽, 车站分工

Abstract:

To make comprehensive use of the passenger transportation resources in a high-speed railway hub, this study explores the division of labor among passenger stations within a high-speed railway hub. Herein, a multiobjective programming model was developed with the objectives of minimizing the total train operation time and coordinating the capacities of the stations in the hub. The augmented ε-constraint algorithm was used to solve the approximate nondominated frontier of the model. Using the Zhengzhou high-speed railway hub as a case study, the differences between the existing plan and the optimized plan and their adaptabilities were qualitatively and quantitatively compared to validate the feasibility and effectiveness of the proposed model and algorithm. The results show that the augmented ε-constraint algorithm can identify high-quality representative nondominated solutions for the proposed model. Moreover, the optimized plan can reduce the train operation time within the hub and enhance the coordination of station capacity utilization. Thus, this study provides reliable references and reasonable suggestions for decision-making regarding capacity expansion, transformation, and optimization of high-speed railway hub areas.

Key words: railway transportation, capacity utilization, multi-objective optimization, high-speed railway hub, division of labor among stations

中图分类号: 

  • U291.7

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