• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
XU Chang’an, NI Shaoquan, CHEN Dingjun. Collaborative Optimization for Timetable and Maintenance Window Based on Two-Stage Algorithm[J]. Journal of Southwest Jiaotong University, 2020, 55(4): 882-888. doi: 10.3969/j.issn.0258-2724.20180577
Citation: XU Chang’an, NI Shaoquan, CHEN Dingjun. Collaborative Optimization for Timetable and Maintenance Window Based on Two-Stage Algorithm[J]. Journal of Southwest Jiaotong University, 2020, 55(4): 882-888. doi: 10.3969/j.issn.0258-2724.20180577

Collaborative Optimization for Timetable and Maintenance Window Based on Two-Stage Algorithm

doi: 10.3969/j.issn.0258-2724.20180577
  • Received Date: 09 Jul 2018
  • Rev Recd Date: 14 Dec 2018
  • Available Online: 19 Dec 2018
  • Publish Date: 01 Aug 2020
  • There is mutual coupling between train timetable generation and maintenance window setting. To achieve the purpose of optimizing the train timetable structure and reasonably configuring the railway transportation capacity. According to the dynamic analysis of train timetable generation and maintenance window setting, the minimum impact of maintenance windows setting on train timetable planning is used as the objective function, and a mixed integer programming (MIP) model is built to realize the collaborative optimization of train timetable and maintenance window. To solve this complex problem, a two-stage solving algorithm including preliminary optimization and comprehensive optimization is designed. In the preliminary optimization stage, a heuristic algorithm based on experts’ experience is used to obtain the general framework of the train timetable. In the comprehensive optimization stage, the tabu search algorithm is used to obtain the global optimal solution. Finally, a case study based on Baoji−Chengdu railway line (Yangpingguan−Chengdu section) was conducted to verify the model. The results show that compared with the timetable compiled by human-computer interaction, the proposed method can effectively reduce the total residence time of all passenger and freight trains at stations by 6.19%, a total reduction of 1 355 min, of which the passenger trains and freight trains station residence time are decreased by 3.08% and 7.40%, with the total reduction time of 189 min and 1 166 min, respectively.

     

  • 史峰,黎新华,秦进,等. 单线列车运行图铺划的时间循环迭代优化方法[J]. 铁道学报,2005,27(1): 1-5. doi: 10.3321/j.issn:1001-8360.2005.01.001

    SHI Feng, LI Xinhua, QIN Jin, et al. Time-cycle iterative optimization method for single-line train timetable planning[J]. Journal of the China Railway Society, 2005, 27(1): 1-5. doi: 10.3321/j.issn:1001-8360.2005.01.001
    徐长安,倪少权,陈钉均,等. 天窗设置理论与优化技术研究综述[J]. 交通运输工程与信息学报,2017,15(4): 24-31. doi: 10.3969/j.issn.1672-4747.2017.04.004

    XU Changan, NI Shaoquan, CHEN Dingjun, et al. Survey of optimization theory and method of maintenance window arrangement in the train timetable[J]. Journal of Transportation Engineering and Information, 2017, 15(4): 24-31. doi: 10.3969/j.issn.1672-4747.2017.04.004
    FORSGREN M, ARONSSON M, GESTRELIUS S. Maintaining tracks and traffic flow at the same time[J]. Journal of Rail Transport Planning & Management, 2013, 3(3): 111-123.
    ALBRECHT A R, PANTON D M, LEE D H. Rescheduling rail networks with maintenance disruptions using problem space search[J]. Computers and Operations Research, 2013, 40(3): 703-712. doi: 10.1016/j.cor.2010.09.001
    LIDEN T, JOBORN M. An optimization model for integrated planning of railway traffic and network maintenance[J]. Transportation Research Part C:Emerging Technologies, 2017, 74: 327-347. doi: 10.1016/j.trc.2016.11.016
    AKEN S V, BESINOVIC N, GOVERDE R M P. Designing alternative railway timetables under infrastructure maintenance possessions[J]. Transportation Research Part B:Methodological, 2017, 98: 224-238. doi: 10.1016/j.trb.2016.12.019
    赵丽珍,赵映莲,杨岳勤,等. 高速铁路综合维修“天窗”开设形式与行车组织协调问题的研究[J]. 中国铁道科学,2002,23(2): 127-131. doi: 10.3321/j.issn:1001-4632.2002.02.021

    ZHAO Lizhen, ZHAO Yinglian, YANG Yueqin, et al. Study on the coordination of the opening form and the organization of trains in the comprehensive maintenance of high-speed railway[J]. China Railway Science, 2002, 23(2): 127-131. doi: 10.3321/j.issn:1001-4632.2002.02.021
    聂磊,胡必松,付慧伶,等. 客运专线夜间行车与天窗的相互影响分析[J]. 交通运输系统工程与信息,2010,10(5): 66-72. doi: 10.3969/j.issn.1009-6744.2010.05.009

    NIE Lei, HU Bisong, FU Huizhen, et al. Analysis of interaction between night driving and skylight in passenger dedicated line[J]. Journal of Transportation Systems Engineering and Information, 2010, 10(5): 66-72. doi: 10.3969/j.issn.1009-6744.2010.05.009
    杨奎,彭其渊,鲁工圆,等. 高速铁路天窗设置与夜间列车运行协调优化技术[J]. 铁道学报,2015(4): 1-7. doi: 10.3969/j.issn.1001-8360.2015.04.001

    YANG Kui, PENG Qiyuan, LU Gongyuan, et al. Coordination optimization technology of skylight setting and night train operation in high speed railway[J]. Journal of the China Railway Society, 2015(4): 1-7. doi: 10.3969/j.issn.1001-8360.2015.04.001
    张强锋,吕红霞,杨宇翔. 基于三角模糊数的高铁天窗施工实施效果评价[J]. 西南交通大学学报,2018,53(4): 798-805. doi: 10.3969/j.issn.0258-2724.2018.04.018

    ZHANG Qiangfeng, LÜ Hongxia, YANG Yuxiang. Effect evaluation of high-speed railway skylight construction based on triangular fuzzy number[J]. Journal of Southwest Jiaotong University, 2018, 53(4): 798-805. doi: 10.3969/j.issn.0258-2724.2018.04.018
    兰泽康,何世伟,黎浩东,等. 考虑维修天窗和到发线数量的复线铁路列车运行图优化[J]. 北京交通大学学报,2018,42(3): 30-36.

    LAN Zekang, HE Shiwei, LI Haodong, et al. Optimization for double-track railway train timetabling considering the maintenance skylight and the number of arrival-departure tracks[J]. Journal of Beijing Jiaotong University, 2018, 42(3): 30-36.
    倪少权. 中国铁路列车运行图编制系统研究[D]. 成都: 西南交通大学, 2013
    董守清,王进勇,闫海峰. 双线铁路列车运行调整的禁忌搜索算法[J]. 中国铁道科学,2005,26(4): 114-119. doi: 10.3321/j.issn:1001-4632.2005.04.024

    DONG Shouqing, WANG Jinyong, YAN Haifeng. Tabu search algorithm for train operation adjustment of two-line railway[J]. China Railway Science, 2005, 26(4): 114-119. doi: 10.3321/j.issn:1001-4632.2005.04.024
  • Relative Articles

    [1]XU Chang’an, LI Shengdong, LI Sihan, NI Shaoquan. Collaborative Optimization for Overnight Train Operation and Maintenance Window Setting of High-Speed Railways[J]. Journal of Southwest Jiaotong University, 2021, 56(4): 744-751. doi: 10.3969/j.issn.0258-2724.20191205
    [2]ZHOU Wenliang, LI Peng, TIAN Junli, DENG Lianbo. Optimization of Train Timetable for Intercity Railway Based on Coordinated Operation of Multi-periodic Trains[J]. Journal of Southwest Jiaotong University, 2019, 54(4): 831-839. doi: 10.3969/j.issn.0258-2724.20170153
    [3]ZHANG Xiaobing, NI Shaoquan, PAN Jinshan. Optimization of Train Diagram Structure for High-Speed Railway[J]. Journal of Southwest Jiaotong University, 2016, 29(5): 938-943. doi: 10.3969/j.issn.0258-2724.2016.05.017
    [4]HUANG Jian, PENG Qiyuan. Two-Stage Optimization Algorithm for Stop Schedule Plan of High-Speed Train[J]. Journal of Southwest Jiaotong University, 2012, 25(3): 484-489. doi: 10.3969/j.issn.0258-2724.2012.03.021
    [5]ZHANG Jing, LI Bai-Lin, ZHANG Wei-Hua, LIU Yong-Jun. Improved Collaborative Optimization Algorithm[J]. Journal of Southwest Jiaotong University, 2010, 23(4): 539-543. doi: 10. 3969/ j. issn. 0258-2724.
    [6]LI Jian, LU Zhixiong, GAO Mourong. New Tabu Search Algorithm for Large-Scale Vehicle Routing Problem with Simultaneous Deliveries and Pickups[J]. Journal of Southwest Jiaotong University, 2009, 22(5): 787-793.
    [7]TAO Ran, LÜ, Hongxia, CHEN Guangxiu. Model and Algorithm for Making Locomotive Working Diagram Based on Multiple Traveling Salesmen Problem[J]. Journal of Southwest Jiaotong University, 2006, 19(5): 653-657.
    [8]NIShao-quan, L Hong-xia, YANGMing-lun. Research on Design of Train Diagram-Making System of Railways in China[J]. Journal of Southwest Jiaotong University, 2003, 16(3): 332-335.
    [9]NIShao-quan, L Hong-xia, LIUJi-yong. Design and Implementation of an Adjusting System of Computerized Train Graph Systems[J]. Journal of Southwest Jiaotong University, 2001, 14(3): 240-244.
    [10]SHUAIBin, QINGXue-jiang. The Frame Design of Making Train Diagram System with Computer Based on OOP[J]. Journal of Southwest Jiaotong University, 2000, 13(3): 259-263.
    [11]XIQing. Layout on Distributed Database System for Programming Train Diagram by Computer[J]. Journal of Southwest Jiaotong University, 2000, 13(3): 264-267.
    [12]DUWen, RENMin. Some of Thinking for Reforming Railway Transport Products Statistics[J]. Journal of Southwest Jiaotong University, 2000, 13(3): 246-249.
    [13]PENG Qi-yuan, WANGJun, CUIXian-bo. Design on the Access to Distributed Database of the Network Train Diagram System[J]. Journal of Southwest Jiaotong University, 2000, 13(3): 268-272.
    [14]LI Zong-ping, LIUHai-yan, DUWen. On the Model for Production Optimal Decision of Railway Transport Products[J]. Journal of Southwest Jiaotong University, 2000, 13(3): 242-245.
    [15]JIANGNan, TANZhong-ping, HEFu. A Study on Correlation Searching System for the Laws and Regulations in Railway Transportation[J]. Journal of Southwest Jiaotong University, 2000, 13(4): 413-416.
    [16]YAN Yu-song. The Genetic Algorithms for the Carrying Capacity of Parallel Train Working Graph on Single Railway Lines[J]. Journal of Southwest Jiaotong University, 2000, 13(3): 277-279.
  • Cited by

    Periodical cited type(7)

    1. 邢春阳,蓝天,高德钊,陈磊,赵敏敏. 基于客流量分析的增开地铁列车运行图局部调整模型设计. 自动化与仪器仪表. 2024(03): 110-113+118 .
    2. 石贇,牟海波,黄志鹏,董文青,柴获. 考虑跨线列车的运行图与天窗一体化模型与算法. 铁道科学与工程学报. 2024(05): 1761-1773 .
    3. 刘磊,田志强,靳欣妮,李津铭. 高原地区客货共线铁路综合维修天窗设置研究. 铁道技术标准(中英文). 2024(05): 45-52 .
    4. 杨皓男,倪少权,潘金山,吕苗苗,邓洪波,陈钉均. 铁路天窗方案与列车运行图协同优化研究综述. 铁道运输与经济. 2024(11): 71-81+174 .
    5. 刘俊琦,张则强,龚举华,张裕. 受约束的过道布置问题建模及优化方法. 西南交通大学学报. 2022(06): 1376-1385 . 本站查看
    6. 徐长安,李晟东,李斯涵,倪少权. 高铁夕发朝至列车开行与天窗设置协同优化. 西南交通大学学报. 2021(04): 744-754 . 本站查看
    7. 李彪,王立文,邢志伟,王思博,罗谦. 飞机地面除冰资源协同控制. 上海交通大学学报. 2021(11): 1362-1370 .

    Other cited types(10)

  • Created with Highcharts 5.0.7Amount of accessChart context menuAbstract Views, HTML Views, PDF Downloads StatisticsAbstract ViewsHTML ViewsPDF Downloads2024-042024-052024-062024-072024-082024-092024-102024-112024-122025-012025-022025-0305101520
    Created with Highcharts 5.0.7Chart context menuAccess Class DistributionFULLTEXT: 37.7 %FULLTEXT: 37.7 %META: 58.3 %META: 58.3 %PDF: 4.1 %PDF: 4.1 %FULLTEXTMETAPDF
    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 6.2 %其他: 6.2 %Kennedy Town: 0.2 %Kennedy Town: 0.2 %Trenton: 0.3 %Trenton: 0.3 %[]: 0.2 %[]: 0.2 %上海: 0.6 %上海: 0.6 %东莞: 0.5 %东莞: 0.5 %临汾: 0.3 %临汾: 0.3 %乐山: 0.3 %乐山: 0.3 %六安: 0.3 %六安: 0.3 %内江: 0.6 %内江: 0.6 %加利福尼亚州: 0.3 %加利福尼亚州: 0.3 %北京: 4.4 %北京: 4.4 %十堰: 0.2 %十堰: 0.2 %南京: 0.3 %南京: 0.3 %南昌: 0.2 %南昌: 0.2 %台州: 0.5 %台州: 0.5 %合肥: 0.2 %合肥: 0.2 %天津: 0.8 %天津: 0.8 %太原: 0.3 %太原: 0.3 %宣城: 0.2 %宣城: 0.2 %广州: 0.2 %广州: 0.2 %张家口: 1.9 %张家口: 1.9 %成都: 3.7 %成都: 3.7 %成都市青羊区: 0.3 %成都市青羊区: 0.3 %昆明: 0.2 %昆明: 0.2 %杭州: 0.3 %杭州: 0.3 %格兰特县: 0.2 %格兰特县: 0.2 %武汉: 0.3 %武汉: 0.3 %江门: 0.3 %江门: 0.3 %池州: 1.0 %池州: 1.0 %沈阳: 0.3 %沈阳: 0.3 %沧州: 0.2 %沧州: 0.2 %洛阳: 0.3 %洛阳: 0.3 %深圳: 0.5 %深圳: 0.5 %漯河: 1.3 %漯河: 1.3 %石家庄: 0.5 %石家庄: 0.5 %福州: 0.2 %福州: 0.2 %芒廷维尤: 18.6 %芒廷维尤: 18.6 %芝加哥: 0.2 %芝加哥: 0.2 %营口: 0.3 %营口: 0.3 %西宁: 44.7 %西宁: 44.7 %诺沃克: 0.3 %诺沃克: 0.3 %贵阳: 0.3 %贵阳: 0.3 %达州: 0.2 %达州: 0.2 %运城: 1.0 %运城: 1.0 %通辽: 0.2 %通辽: 0.2 %遵义: 0.5 %遵义: 0.5 %郑州: 0.6 %郑州: 0.6 %重庆: 0.3 %重庆: 0.3 %铁岭: 0.2 %铁岭: 0.2 %长春: 0.2 %长春: 0.2 %长沙: 3.4 %长沙: 3.4 %青岛: 0.5 %青岛: 0.5 %其他Kennedy TownTrenton[]上海东莞临汾乐山六安内江加利福尼亚州北京十堰南京南昌台州合肥天津太原宣城广州张家口成都成都市青羊区昆明杭州格兰特县武汉江门池州沈阳沧州洛阳深圳漯河石家庄福州芒廷维尤芝加哥营口西宁诺沃克贵阳达州运城通辽遵义郑州重庆铁岭长春长沙青岛

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(4)  / Tables(1)

    Article views(756) PDF downloads(29) Cited by(17)
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return