Volume 20 Issue 5
. 
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2020  >  20(5): 187-197
ZHANG Na, YANG Qi, HU Fei-hu, JIANG Xin-yu, LIU Yong-xiong. Vehicle scheduling model considering individual driving speed deviation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(5): 187-197. doi: 10.19818/j.cnki.1671-1637.2020.05.015
Citation: ZHANG Na, YANG Qi, HU Fei-hu, JIANG Xin-yu, LIU Yong-xiong. Vehicle scheduling model considering individual driving speed deviation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(5): 187-197. doi: 10.19818/j.cnki.1671-1637.2020.05.015
shu

Vehicle scheduling model considering individual driving speed deviation

doi: 10.19818/j.cnki.1671-1637.2020.05.015
  • 1.

    College of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China

  • 2.

    School of Humanities, Chang'an University, Xi'an 710064, Shaanxi, China

  • 3.

    Moody College of Communication, The University of Texas at Austin, Austin TX78705, Texas, USA

  • 4.

    School of Economics and Management, Chang'an University, Xi'an 710064, Shaanxi, China

  • 5.

    School of Electric Engineering, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China

  • 6.

    School of Information Engineering, Chang'an University, Xi'an 710064, Shaanxi, China

Funds:

National Natural Science Foundation of China 71732006

National Natural Science Foundation of China 61174154

Social Science Foundation of Shaanxi Province 2019S032

Fundamental Research Funds for the Central Universities 310833160212

Sichuan Major Project of Science and Technology Achievements Transter Demonstration 21ZHSF0055

More Information
    Abstract
  • In view of driving speed deviation, a vehicle scheduling model was established for multi-drivers, multi-vehicles, multi-materials, multi-depots, and multi-demands targeting at the shortest overall transportation time, the lowest overall transportation cost and the least multi-objective overall transportation time and cost, respectively. The effects of individual driving speed deviation on the above targets were studied. The driver parameters were input into the gene coding of the genetic algorithm. The constraints of driver uniqueness, initial location, and the supply and demand quantities of materials were established to ensure that the distribution scheme of drivers in each gene was feasible and the material transportation did not exceed the total supply and demand. A genetic algorithm was applied to solve the vehicle scheduling schemes for each target with and without driving speed deviation under the condition of randomly assigned drivers. Calculation result shows that the optimized scheduling schemes satisfy all the constraints in the model. For the three optimal schemes, the driver assignments are different, indicating that the target function is affected by the driving speed deviation. The dispatching results of each target with driving speed deviation are superior to those without driving speed deviation. The difference ratios of the three objective functions are 3.5%, 2.96% and 1.13%, respectively, which shows that the driving speed deviation has a certain influence on the solving quality. The target scheduling results of the driver's random assignment are inferior to the corresponding optimal results. The different ratios of the three objective functions are 3.91%, 2.47% and 1.98%, respectively, showing that the dispatching efficiency is affected by the driving speed deviation, and optimizing the driver allocation scheme can reduce the overall transport time and cost. Analysis result shows that the vehicle scheduling scheme, which is more in line with the scheduling target, closer to reality, and more economical and time-saving, can be obtained by allocating drivers reasonably according to the specific dispatching target.

     

    • FullText(HTML)
  • loading
    • References(35)
  • [1]
    BRAEKERS K, RAMAEKERS K, VAN N I. The vehicle routing problem: state of the art classification and review[J]. Computers and Industrial Engineering, 2016, 99: 300-313. doi: 10.1016/j.cie.2015.12.007
    [2]
    王万良, 黄海鹏, 赵燕伟, 等. 基于车辆共享的软时间窗动态需求车辆路径问题[J]. 计算机集成制造系统, 2011, 17(5): 1056-1063. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201105020.htm

    WANG Wan-liang, HUANG Hai-peng, ZHAO Yan-wei, et al. Dynamic customer demand VRP with soft time windows based on vehicle sharing[J]. Computer Integrated Manufacturing Systems, 2011, 17(5): 1056-1063. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201105020.htm
    [3]
    BERGHIDA M, BOUKRA A. EBBO: an enhanced biogeography-based optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows[J]. International Journal of Advanced Maufacturing Technology, 2015, 77(9/10/11/12): 1711-1725.
    [4]
    ADELZADEH M, ASl V M, KOOSHA M. A mathematical model and a solving procedure for multi-depot vehicle routing problem with fuzzy time window and heterogeneous vehicle[J]. International Journal of Advanced Maufacturing Technology, 2014, 75(5/6/7/8): 793-802.
    [5]
    DA SILVA JÚNIOR O S, LEAL J E, REIMANN M. A multiple ant colony system with random variable neighborhood descent for the dynamic vehicle routing problem with time windows[J]. Soft Computing, 2020, DOI: 10.1007/s00500-020-05350-4.
    [6]
    MADANKUMAR S, RAJENDRAN C. A mixed integer linear programming model for the vehicle routing problem with simultaneous delivery and pickup by heterogeneous vehicles, and constrained by time windows[J]. Sadhana—Academy Proceedings in Engineering Sciences, 2019, 44(2): UNSP39-1-39.
    [7]
    LIU Ran, JIANG Zhi-bin. A constraint relaxation-based algorithm for the load-dependent vehicle routing problem with time windows[J]. Flexible Services and Manufacturing Journal, 2019, 31(2): 331-353. doi: 10.1007/s10696-018-9323-0
    [8]
    KIRCI P. An optimization algorithm for a capacitated vehicle routing problem with time windows[J]. Sadhana—Academy Proceedings in Engineering Sciences, 2016, 41(5): 519-529.
    [9]
    WEN L, EGLESE R. Minimum cost VRP with time-dependent speed data and congestion charge[J]. Computers and Operations Research, 2015, 56: 41-50. doi: 10.1016/j.cor.2014.10.007
    [10]
    胡飞虎, 马贝龙, 杨丽, 等. 基于改进遗传算法的应急物资配送车辆调度优化问题研究[J]. 计算机应用研究, 2014, 31(10): 2928-2932. doi: 10.3969/j.issn.1001-3695.2014.10.010

    HU Fei-hu, MA Bei-long, YANG Li, et al. Research on vehicle scheduling optimization in emergency material distribution based on improved genetic algorithm[J]. Application Research of Computers, 2014, 31(10): 2928-2932. (in Chinese). doi: 10.3969/j.issn.1001-3695.2014.10.010
    [11]
    陈钢铁, 帅斌. 基于模糊网络和时间依赖的应急车辆调度优化研究[J]. 中国安全科学学报, 2011, 21(8): 171-176. doi: 10.3969/j.issn.1003-3033.2011.08.027

    CHEN Gang-tie, SHUAI Bin. Research on emergency vehicle scheduling optimization based on fuzzy network and time dependence[J]. China Safety Science Journal, 2011, 21(8): 171-176. (in Chinese). doi: 10.3969/j.issn.1003-3033.2011.08.027
    [12]
    SRINIVAS S S, GAJANAND M S. Vehicle routing problem and driver behaviour: a review and framework for analysis[J]. Transport Reviews, 2017, 37(5): 590-611. doi: 10.1080/01441647.2016.1273276
    [13]
    SCHNEIDER M. The vehicle-routing problem with time windows and driver-specific times[J]. European Journal of Operational Research, 2016, 250(1): 101-119. doi: 10.1016/j.ejor.2015.09.015
    [14]
    LIGHTNERLAWS C, AGRAWAL V, LIGHTNER C, et al. An evolutionary algorithm approach for the constrained multi-depot vehicle routing problem[J]. International Journal of Intelligent Computing and Cybernetics, 2016, 9(1): 2-22. doi: 10.1108/IJICC-06-2015-0018
    [15]
    AGRAWAL V, LIGHTNER C, LIGHTNERLAWS C, et al. A bi-criteria evolutionary algorithm for a constrained multi-depot vehicle routing problem[J]. Soft Computing, 2017, 21(17): 5159-5178. doi: 10.1007/s00500-016-2112-3
    [16]
    MANCINI S. The hybrid vehicle routing problem[J]. Transportation Research Part C: Emerging Technologies, 2017, 78: 1-12. doi: 10.1016/j.trc.2017.02.004
    [17]
    KOULAEIAN M, SEIDGAR H, KIANI M, et al. A multi-depot simultaneous pickup and delivery problem with balanced allocation of routes to drivers[J]. International Journal of Industrial Engineering: Theory Applications and Practice, 2015, 22(2): 223-242.
    [18]
    DREXL M, RIECK J, SIGL T, et al. Simultaneous vehicle and crew routing and scheduling for partial- and full-load long-distance road transport[J]. Business Research, 2013, 6(2): 242-264. doi: 10.1007/BF03342751
    [19]
    KOK A L, MEYER C M, KOPFER H, et al. A dynamic programming heuristic for the vehicle routing problem with time windows and European Community social legislation[J]. Transportation Science, 2010, 44(4): 442-454. doi: 10.1287/trsc.1100.0331
    [20]
    YOUSEFIKHOSHBAKHT M, DIDEHVAR F, RAHMATI F. An effective rank based ant system algorithm for solving the balanced vehicle routing problem[J]. International Journal of Industrial Engineering—Theory Application and Practice, 2016, 23(1): 13-25.
    [21]
    杨群, 赵亚男, 张国伍, 等. 基于模糊规则的货运车调度方法[J]. 系统工程理论与实践, 2002(5): 125-127. doi: 10.3321/j.issn:1000-6788.2002.05.023

    YANG Qun, ZHAO Ya-nan, ZHANG Guo-Wu, et al. Freight car scheduling method based on fuzzy rules[J]. System Engineering Theory and Practice, 2002(5): 125-127. (in Chinese). doi: 10.3321/j.issn:1000-6788.2002.05.023
    [22]
    GEE S B, AROKIASAMI W A, JIANG J, et al. Decomposition-based multi-objective evolutionary algorithm for vehicle routing problem with stochastic demands[J]. Soft Computing, 2016, 20(9): 3443-3453. doi: 10.1007/s00500-015-1830-2
    [23]
    曹剑东. 模糊条件下市区集送货的计算机辅助调度[D]. 北京: 清华大学, 2008.

    CAO Jian-dong. Computer aided dispatch for city pickup and delivery under fuzzy condition[D]. Beijing: Tsinghua University, 2008. (in Chinese).
    [24]
    许茂增, 余国印, 周翔, 等. 综合成本最小的低碳车辆调度问题及算法[J]. 计算机集成制造系统, 2015, 21(7): 1906-1914. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201507028.htm

    XU Mao-zeng, YU Guo-yin, ZHOU Xiang, et al. Low-carbon vehicle scheduling problem and algorithm with minimum-comprehendsive-cost[J]. Computer Integrated Manufacturing System, 2015, 21(7): 1906-1914. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201507028.htm
    [25]
    GOEL A. The minimum duration truck driver scheduling problem[J]. EURO Journal on Transportation and Logistics, 2012, 1(4): 285-306. doi: 10.1007/s13676-012-0014-9
    [26]
    TAVAKKOLI-MOGHADDAM R, ALINAGHIAN M, SALAMAT-BAKHSH A, et al. A hybrid meta-heuristic algorithm for the vehicle routing problem with stochastic travel times considering the driver's satisfaction[J]. Journal of Industrial Engineering International, 2012, 8(4): 1-6.
    [27]
    GHASEMI NOUGHAB M, SADEGHI A, MOHAMMADZADEH MOGHADDAM A, et al. Fatigue risk management: assessing and ranking the factors affecting the degree of fatigue and sleepiness of heavy-vehicle drivers using TOPSIS and statistical analyses[J]. Iranian Journal of Science and Technology—Transactions of Civil Engineering, 2020, 44(4): 1345-1357. doi: 10.1007/s40996-019-00320-9
    [28]
    徐福博. 基于IC卡数据的公交运行速度差异分析[J]. 汽车实用技术, 2018(16): 94-95. https://www.cnki.com.cn/Article/CJFDTOTAL-SXQC201816034.htm

    XU Fu-bo. Analysis of bus speed difference based on IC card data[J]. Automobile Applied Technology, 2018(16): 94-95. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SXQC201816034.htm
    [29]
    李长城, 刘小明, 荣建, 等. 不同能见度条件下高速公路车辆速度特性研究[J]. 交通运输系统工程与信息, 2014, 14(6): 213-218. doi: 10.3969/j.issn.1009-6744.2014.06.035

    LI Chang-cheng, LIU Xiao-ming, RONG Jian, et al. Characteristics of vehicle speed for expressway under different visibility condition[J]. Journal of Transportation Systems Engineering and Information Technology, 2014, 14(6): 213-218. (in Chinese). doi: 10.3969/j.issn.1009-6744.2014.06.035
    [30]
    AKIN D, SISIOPKU V P, SKABARDONIS A. Impacts of weather on traffic flow characteristics of urban freeways in Istanbul[C]∥Elsevier. 6th International Symposium on Highway Capacity and Quality of Service. Amsterdam: Elsevier, 2011: 89-99.
    [31]
    陈皓, 张磊. 基于大数据的出租车与普通小汽车行驶速度差异研究[J]. 公路, 2017(2): 147-152. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201702029.htm

    CHEN Hao, ZHANG Lei. Research on the difference of taxi and car speed based on big data[J]. Highway, 2017(2): 147-152. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201702029.htm
    [32]
    谢涛, 陈火旺, 康立山. 多目标优化的演化算法[J]. 计算机学报, 2003, 23(8): 997-1003. doi: 10.3321/j.issn:0254-4164.2003.08.015

    XIE Tao, CHEN Huo-wang, KANG Li-shan. Evolutionary algorithms of multi-objective optimization problems[J]. Chinese Journal of Computers, 2003, 23(8): 997-1003. (in Chinese). doi: 10.3321/j.issn:0254-4164.2003.08.015
    [33]
    张栋亭. 多目标优化与模糊决策在混流装配排序中的应用[D]. 武汉: 华中科技大学, 2008.

    ZHANG Dong-ting. Application of multi-objective optimization and fuzzy decision-making for mixed-model assembly sequencing[D]. Wuhan: Huazhong University of Science and Technology, 2008. (in Chinese).
    [34]
    《中国公路学报》编辑部. 中国交通工程学术研究综述: 2016[J]. 中国公路学报, 2016, 29(6): 1-161. doi: 10.3969/j.issn.1001-7372.2016.06.001

    Editorial Department of China Journal of Highway and Transport. Review on China's traffic engineering research progress: 2016[J]. China Journal of Highway and Transport, 2016, 29(6): 1-161. (in Chinese). doi: 10.3969/j.issn.1001-7372.2016.06.001
    [35]
    TREIBER M, HELBING D. Macroscopic simulation of widely scattered synchronized traffic states[J]. Journal of Physics A—Mathematical and General, 1999, 32(1): 17-23. doi: 10.1088/0305-4470/32/1/003
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

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
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (1004) PDF downloads(293) Cited by()
    Proportional views
    Related

    Copyright《Journal of Traffic and Transportation Engineering》编辑部陕ICP备05001904号-1

    Address ：Editorial Department of Journal of Traffic and Transportation Engineering, Chang 'an University, Middle Section of South Second Ring Road, Xi 'an, Shaanxi（710064） Tel：029-82334388 Email：jygc@chd.edu.cn

    All visit:Today's visit:

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return