• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2016, Vol. 38 ›› Issue (03): 507-513.

• 论文 • 上一篇    下一篇

基于改进遗传算法的赶流列车运行调整研究

陈东1,彭其渊2,张燕1,李永辉1   

  1. (1.西南交通大学峨眉校区交通运输系,四川 峨眉 614202;2.西南交通大学交通运输与物流学院,四川 成都 610031)
  • 收稿日期:2015-04-10 修回日期:2015-06-26 出版日期:2016-03-25 发布日期:2016-03-25
  • 基金资助:

    国家自然科学基金(U1234206);中国铁路总公司科技研究开发计划课题(2014X009F);教育部春晖计划(Z2014071)

Train operation adjustment using
an improved genetic algorithm  

CHEN Dong1,PENG Qiyuan2,ZHANG Yan1,LI Yonghui1   

  1.  (1.Traffic Transportation Department,Emei Campus of Southwest Jiaotong University,Emei  614202;
    2.School of Transportation and Logistics,Southwest Jiaotong University,Chendu  610031,China)
  • Received:2015-04-10 Revised:2015-06-26 Online:2016-03-25 Published:2016-03-25

摘要:

开展技术站车流组织与区段列车运行调整的协同优化研究,利用在途列车的运行可调性实现运输区域的“线流配合”,可优化运输生产指标。将前方技术站的车流接续需求作为列车运行调整的目标之一,并定义为赶流调整。在分析赶流调整策略及应用场景的基础上,建立了赶流调整模型,设计了基于遗传算法的模型求解算法。算法设计充分结合列车运行调整特点,有效避免了“早熟”及收敛速度慢等现象,适应性好,求解时间能很好地满足列车运行调整需求。可快速验证“线流配合”研究思路中调整目标的可行性,并给出具体的调整措施,为技术站车流组织与列车运行调整协同优化研究的深入奠定基础。

关键词: 铁路运输, 运行调整, 车流接续, 遗传算法, 线流配合, 调整策略

Abstract:

We study the collaborative optimization of wagon flow organization in technical stations and train operation adjustment in sections, realize “flow and line integration” of transportation regions by adjusting the trains on the way, thus obtaining better transportation production index. We take the wagon flow requirements of the forward technical station as one of the objectives of train operation adjustment and refer it as matching flow adjustment. Analyzing the matching flow adjustment strategies and their application scenarios, we build a matching flow model and design the solving algorithm based on the improved genetic algorithm. The algorithm design fully integrates the features of train operation adjustment and effectively avoids problems of premature and slow convergence. It has good applicability with acceptable computation time. The feasibility of the adjustment targets can be quickly verified, and specific adjustment measures are then proposed. Our findings lay a foundation for further study on the collaborative optimization of wagon flow organization and train operation adjustment in technical stations.

Key words: railway transportation;operation adjustment;wagon flow connection;genetic algorithm;flow and line integration;strategy adjustment