Volume 12 Issue 3
. 
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2012  >  12(3): 86-91
Next Previous
LI Guang-ru, YANG Da-ben, REN Da-wei. Path optimization algorithm of dynamic scheduling for container truck[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 86-91. doi: 10.19818/j.cnki.1671-1637.2012.03.013
Citation: LI Guang-ru, YANG Da-ben, REN Da-wei. Path optimization algorithm of dynamic scheduling for container truck[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 86-91. doi: 10.19818/j.cnki.1671-1637.2012.03.013
shu

Path optimization algorithm of dynamic scheduling for container truck

doi: 10.19818/j.cnki.1671-1637.2012.03.013
  • 1.

    School of Navigation, Dalian Maritime University, Dalian 116026, Liaoning, China

  • 2.

    Ship Survey Department, Maritime Safety Administration of the People's Republic of China, Beijing 100023, China

More Information
  • Author Bio:

    LI Guang-ru (1970-), male, associate professor, PhD, +86-411-84724329, liguangru@sina.com

  • Received Date: 2012-01-09
  • Publish Date: 2012-06-25
    Abstract
  • From the point of integrated scheduling, the dynamic scheduling method of whole terminal operating field was analyzed, and a new adaptive ant colony optimization of dynamic scheduling for container truck was put out.The GPRS system of terminal was used, and the perception chain was set up by using related data such as the speed, flow and position of container truck.Through judging obstruction status and adjusting feasible point set, the calculation methods of updating strategy and transition probability for pheromone concentration were determined.Aiming at the complexity of terminal road network and the real-time calculation efficiency of ant colony optimization, the steps of ant colony optimization were designed.The information entropy was introduced into ant colony optimization, the MATLAB software was used, and the simulation calculation of dynamic scheduling method for container truck was carried out.Simulation result shows that when the initial speeds of container trucks are 50, 75 km·h-1 respectively and the initial flows of container trucks are 800, 1 000 veh·h-1 respectively, the shortest driving path of container truck is 4.3 km, and the driving time is 0.057 h.The optimal driving path of container truck is 8.3 km, and the driving time is 0.111 h.By using the proposed algorithm, the obstruction problem of terminal can be remitted effectively, and the utilization ratio of container truck and the operating efficiency of terminal can increase obviously.

     

    • FullText(HTML)
  • loading
    • References(16)
  • [1]
    VIS I F A, DE KOSTER R. Transshipment of containers at a container terminal: an overview[J]. European Journal of Operational Research, 2003, 147(1): 1-16. doi: 10.1016/S0377-2217(02)00293-X
    [2]
    MURTYA K G, LIU Ji-yin, WAN Y W, et al. A decision support system for operations in a container terminal[J]. Decision Support Systems, 2005, 39(3): 309-332. doi: 10.1016/j.dss.2003.11.002
    [3]
    SHOU Yong-yi, LAI Chang-tao, LU Ru-fu, et al. Multi-objective optimization model and ant colony optimization of liner ship scheduling[J]. Journal of Traffic and Transporta-tion Engineering, 2001, 11(4): 84-88. (in Chinese). http://transport.chd.edu.cn/article/id/201104013
    [4]
    ZHANG Hai-lin, JIANG Zhi-bin, XU Hong. A simulation study of container terminal scheduling system[J]. Journal of Shanghai Jiaotong University, 2006, 40(6): 1024-1030. (in Chinese). doi: 10.3321/j.issn:1006-2467.2006.06.033
    [5]
    YU Meng, WANG Shao-mei. Reseach on modeling of multi-agent-based scheduling system for container terminal[J]. Journal of Wuhan University of Technology: Transportation Science and Engineering, 2007, 31(3): 494-498. (in Chinese). doi: 10.3963/j.issn.2095-3844.2007.03.032
    [6]
    HAN Xiao-long, DING Yi-zhong. Simulation system of con-tainer terminal charge/discharge operations[J]. Journal of System Simulation, 2006, 18(8): 2366-2369. (in Chinese). doi: 10.3969/j.issn.1004-731X.2006.08.079
    [7]
    ZHOU Qiang, WANG Meng-chang, YANG Guo-ping, et al. On traffic simulation model of container terminals[J]. Port and Waterway Engineering, 2007(2): 48-52. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SYGC200702011.htm
    [8]
    ZENG Qing-cheng, YANG Zhong-zhen, LAI Lu-yuan. Models and algorithms for multi-crane oriented scheduling method in container terminals[J]. Transport Policy, 2009, 16(5): 271-278. doi: 10.1016/j.tranpol.2009.08.006
    [9]
    PETERINGA M E H, MURTYB K G. Effect of block length and yard crane deployment systems on overall per-formance at a seaport container transshipment terminal[J]. Computers and Operations Research, 2009, 36(5): 1711-1725. doi: 10.1016/j.cor.2008.04.007
    [10]
    ZHAO Wen-juan, GOODCHILD A V. The impact of truck arrival information on container terminal rehandling[J]. Transportation Research Part E: Logistics and Transportation Review, 2010, 46(3): 327-343. doi: 10.1016/j.tre.2009.11.007
    [11]
    NETO R F T, FILHO M G. A software model to prototype ant colony optimization algorithms[J]. Expert Systems with Applications, 2011, 38(1): 249-259. doi: 10.1016/j.eswa.2010.06.054
    [12]
    YANG Da-ben. GAAA algorithm-based optimized dispatch for container trucks in container terminals[D]. Dalian: Dalian Maritime University, 2010. (in Chinese).
    [13]
    PAN Deng, ZHENG Ying-ping, LU Xiao-fang. Dynamic ant colony algorithm for avoiding congestion on vehicle routes[J]. Computer Engineering, 2008, 34(5): 1-4. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJC200805003.htm
    [14]
    DORIGO M, GAMBARDELLA L M. Ant colony system: a cooperative learning approach to the traveling salesman prob-lem[J]. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 53-66. https://ieeexplore.ieee.org/abstract/document/585892
    [15]
    GAMBARDELLA L M, TAILLARD E, DORIGO M. Ant colonies for the quadratic assignment problem[J]. Journal of the Operational Research Society, 1999, 50(2): 167-176. doi: 10.1057/palgrave.jors.2600676
    [16]
    REIMANN M, DOERNER K, HARTL R F. Ants: savings based ants divide and conquer the vehicle routing problem[J]. Computers and Operations Research, 2004, 31(4): 563-591. https://www.sciencedirect.com/science/article/pii/S0305054803000145
    • Relative Articles
    • Supplements(0)
    • Cited By

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (1023) PDF downloads(956) Cited by()
    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