• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus 收录
  • 全国中文核心期刊
  • 中国科技论文统计源期刊
  • 中国科学引文数据库来源期刊

考虑费用支付模式的公路网养护调度模型

毛新华 王建伟 袁长伟

毛新华, 王建伟, 袁长伟. 考虑费用支付模式的公路网养护调度模型[J]. 西南交通大学学报, 2021, 56(4): 736-743. doi: 10.3969/j.issn.0258-2724.20200192
引用本文: 毛新华, 王建伟, 袁长伟. 考虑费用支付模式的公路网养护调度模型[J]. 西南交通大学学报, 2021, 56(4): 736-743. doi: 10.3969/j.issn.0258-2724.20200192
MAO Xinhua, WANG Jianwei, YUAN Changwei. Maintenance Scheduling Model for Road Networks Considering Payment Modes[J]. Journal of Southwest Jiaotong University, 2021, 56(4): 736-743. doi: 10.3969/j.issn.0258-2724.20200192
Citation: MAO Xinhua, WANG Jianwei, YUAN Changwei. Maintenance Scheduling Model for Road Networks Considering Payment Modes[J]. Journal of Southwest Jiaotong University, 2021, 56(4): 736-743. doi: 10.3969/j.issn.0258-2724.20200192

考虑费用支付模式的公路网养护调度模型

doi: 10.3969/j.issn.0258-2724.20200192
基金项目: 国家自然科学基金(71701022),教育部人文社会科学研究项目(18YJAZH120),陕西省自然科学研究计划项目(2020JQ-360),中央高校基本科研业务费专项资金(300102341513),
详细信息
    作者简介:

    毛新华(1986—),男,副教授,博士,研究方向为公路养护管理,E-mail:maoxinhua@chd.edu.cn

    通讯作者:

    袁长伟(1981—),男,教授,博士,研究方向为基础设施系统建模,E-mail:changwei@chd.edu.cn

  • 中图分类号: U418.2

Maintenance Scheduling Model for Road Networks Considering Payment Modes

  • 摘要: 为使公路养护承包方获取最大的收益现值,研究了业主不同费用支付模式下的路网养护调度问题. 首先,定义了基于时间进度、基于养护进度以及基于养护费用的3种支付模式;其次,构建了以承包方收益现值最大化为目标的养护调度混合整数非线性规划模型,并采用禁忌搜索算法进行求解;最后,通过案例分析验证模型和算法的有效性. 研究结果表明:在3种不同的支付模式下,指派给各养护队的路段以及各路段的养护顺序均有较大的差异;当承包方垫资能力达到一定的水平后,继续提升垫资能力不一定能获得更优的养护调度方案,且无法产生更多的收益现值;业主的支付比例与收益现值之间具有近似单调递增的关系,而折现率与收益现值之间具有负指数关系;增加养护队数量可获取更多的收益现值,但其边际收益逐步降低,只有当承包方的垫资能力和养护队数量同步增长时,才能获取更多的收益现值.

     

  • 图 1  养护施工队指派列表示意

    Figure 1.  Maintenance crew assignment list

    图 2  养护先后顺序列表示意

    Figure 2.  Maintenance sequence list

    图 3  养护施工队指派变换示意

    Figure 3.  Maintenance crew assignment mutation

    图 4  养护先后顺序交换示意

    Figure 4.  Maintenance sequence swap

    图 5  承包方累计净现金流量变化

    Figure 5.  Variation of contractor’s cumulative net cash flow

    图 6  垫资能力敏感性分析

    Figure 6.  Sensitivity analysis of contractor’s advance-fund capacity

    图 7  支付比例敏感性分析

    Figure 7.  Sensitivity analysis ofpayment ratio

    图 8  折现率敏感性分析

    Figure 8.  Sensitivity analysis ofdiscount rate

    图 9  养护队数量敏感性分析

    Figure 9.  Sensitivity analysis of maintenance crews

    表  1  各路段的养护工期、成本及定额

    Table  1.   Duration, maintenance cost and quota of each link

    n线路编号dn/dcn/万元wn/万元n线路编号dn/dcn/万元wn/万元n线路编号dn/dcn/万元wn/万元
    1A1369969I12638817Q1580112
    2B10517210J147410418R115780
    3C12638811K10517219S1686120
    4D147410412L8405620T1791128
    5E179112813M10517221U1791128
    6F158011214N11578022V1580112
    7G13699615O11578023W1791128
    8H147410416P13699624X115780
    下载: 导出CSV

    表  2  最优养护调度方案

    Table  2.   Optimal maintenance scheduling schemes

    支付模式最优养护调度方案支付方案H/万元
    基于时间进度 养护队1:N—L—K—P—E—D—W—J
    养护队2:V—C—Q—F—G—O—T—H
    养护队3:M—X—A—B—R—S—I—U
    支付时间:第29、55、87、105天 ,
    支付额(万元):431.0,456.0,444.0,1014.0
    629.2
    基于养护进度 养护队1:W—V—J—P—H—R—M—L
    养护队2:F—T—U—D—C—G—I
    养护队3:S—E—Q—A—N—O—X—K—B
    支付时间、:第30、58、88、105 ,
    支付额(万元):659.0,498.0,553.0,635.0
    649.1
    基于养护费用 养护队1:U—W—F—G—A—C—R—M
    养护队2:E—Q—H—J—P—X—B—L
    养护队3:T—S—V—D—I—O—N—K
    支付时间:第33、57、84、105天 ,
    支付额(万元):526.0,476.0,551.0,792.0
    645.3
    下载: 导出CSV
  • HACKL J, ADEY B T, LETHANH N. Determination of near-optimal restoration programs for transportation networks following natural hazard events using simulated annealing[J]. Computer-Aided Civil and Infrastructure Engineering, 2018, 33: 618-637.
    CERAVOLO R, MIRAGLIA G, SURACE C. Strategy for the maintenance and monitoring of electric road infrastructures based on recursive lifetime prediction[J]. Journal of Civil Structural Health Monitoring, 2017, 7: 303-314. doi: 10.1007/s13349-017-0227-6
    YU B, GUO Z, PENG Z, et al. Agent-based simulation optimization model for road surface maintenance scheme[J]. Journal of Transportation Engineering,Part B:Pavements, 2019, 145(1): 1-9.
    FONTAINE P, MINNER S. A dynamic discrete network design problem for maintenance planning in traffic networks[J]. Annals of Operations Research, 2017, 253(2): 757-772. doi: 10.1007/s10479-016-2171-y
    SANTOS J, FERREIRA A, FLINTSCH G, et al. A multi-objective optimisation approach for sustainable pavement management[J]. Structure and Infrastructure Engineering, 2018, 14(7): 854-868. doi: 10.1080/15732479.2018.1436571
    ZHANG L, FU L, GU W, et al. A general iterative approach for the system-level joint optimization of pavement maintenance,rehabilitation,and reconstruction planning[J]. Transportation Research Part B:Methodological, 2017, 105: 378-400.
    CHU J C, HUANG K H. Mathematical programming framework for modeling and comparing network-level pavement maintenance strategies[J]. Transportation Research Part B:Methodological, 2018, 109: 1-25.
    TORRES-MACHI C, PELLICER E, YEPES V, et al. Towards a sustainable optimization of pavement maintenance programs under budgetary restrictions[J]. Journal of Cleaner Production, 2017, 148: 90-102.
    DENYSIUK R, MOREIRA A V, MATOS J C, et al. Two-stage multiobjective optimization of maintenance scheduling for pavements[J]. Journal of Infrastructure Systems, 2017, 23(3): 04017001.1-04017001.12.
    ZHANG W, WANG N, NICHOLSON C. Resilience-based post-disaster recovery strategies for road-bridge networks[J]. Structure and Infrastructure Engineering, 2017, 13(11): 1404-1413. doi: 10.1080/15732479.2016.1271813
    LI Y, DONG Y, FRANGOPOL D M, et al. Long-term resilience and loss assessment of highway bridges under multiple natural hazards[J]. Structure and Infrastructure Engineering, 2020, 16(4): 626-641. doi: 10.1080/15732479.2019.1699936
    LI Z, JIN C, HU P, et al. Resilience-based transportation network recovery strategy during emergency recovery phase under uncertainty[J]. Reliability Engineering & System Safety, 2019, 188: 503-514.
    YEPES V, TORRES-MACHI C, CHAMORRO A, et al. Optimal pavement maintenance programs based on a hybrid greedy randomized adaptive search procedure algorithm[J]. Journal of Civil Engineering and Management, 2016, 22(4): 540-550. doi: 10.3846/13923730.2015.1120770
    SCHOBI R, CHATZI E N. Maintenance planning using continuous-state partially observable Markov decision processes and non-linear action models[J]. Structure and Infrastructure Engineering, 2016, 12(8): 977-994.
    KUHN K D. Network-level infrastructure management using approximate dynamic programming[J]. Journal of Infrastructure Systems, 2010, 16(2): 103-111. doi: 10.1061/(ASCE)IS.1943-555X.0000019
    MEDURY A, MADANAT S. Incorporating network considerations into pavement management systems:a case for approximate dynamic programming[J]. Transportation Research Part C:Emerging Technologies, 2013, 33: 134-150.
    DURANGO-COHEN P L, SARUTIPAND P. Maintenance optimization for transportation systems with demand responsiveness[J]. Transportation Research Part C:Emerging Technologies, 2009, 17(4): 337-348.
    OZER H, YANG R, AL-QADI I L. Quantifying sustainable strategies for the construction of highway pavements in Illinois[J]. Transportation Research Part D:Transport and Environment, 2017, 51: 1-13.
    何正文,郑维博,刘人境. 不同支付条件银行授信约束折现流项目调度[J]. 系统工程理论与实践,2016,36(8): 2013-2023. doi: 10.12011/1000-6788(2016)08-2013-11

    HE Zhengwen, ZHENG Weibo, LIU Renjing. Creditconstrained project scheduling with discounted cash flow under different payment terms[J]. System Engineering−Theory and Practice, 2016, 36(8): 2013-2023. doi: 10.12011/1000-6788(2016)08-2013-11
    NABER A. Resource-constrained project scheduling with flexible resource profiles in continuous time[J]. Computers & Operations Research, 2017, 84: 33-45.
    SHAO S, XU S X, HUANG G Q. Variable neighborhood search and tabu search for auction-based waste collection synchronization[J]. Transportation Research Part B:Methodological, 2020, 133(3): 1-20.
  • 加载中
图(9) / 表(2)
计量
  • 文章访问数:  344
  • HTML全文浏览量:  189
  • PDF下载量:  13
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-04-15
  • 修回日期:  2020-07-16
  • 网络出版日期:  2020-08-14
  • 刊出日期:  2021-08-15

目录

    /

    返回文章
    返回