Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition) ›› 2019, Vol. 37 ›› Issue (3): 1-8.doi: 10.16088/j.issn.1001-6600.2019.03.001

   

Time Window Model and Algorithm with AGV System Path Planning

XU Lunhui1,2*,HUANG Baoshan1,ZHONG Haixing2   

  1. 1. Institute of Industrial Automation, Zhuhai Campus, Beijing Institute of Technology,Zhuhai Guangdong 519088,China;
    2. School of Civil and Traffic Engineering, South China University of Technology,Guangzhou Guangdong 510641,China
  • Published:2019-07-12

Abstract: Considering the AGV vehicle speed difference between straight lines and curves in the process of driving,the time window model of the dynamic route planning of AGV system is established to avoid conflict for the two-way single driving lane AGV system operation scene. Taking the combination with the minimum operation cost and priority as the task generation strategy,the algorithm process for the AGV system dynamic path planning time window model is established, which provides an effective method for dynamic path planning problem for multi-AGV system collaborative operation in intelligent logistics and automated storage system under the restriction to minimize the total cost of operation. Case verification shows that this algorithm can effectively plan the path of multiple AGV cooperative operations in the system,so that the system can run at the lowest total cost and reduce the total cost of running the storage system.

Key words: dynamic route planning, intelligent logistics, time window, automatic handing, automated guided vehicle(AGV)

CLC Number: 

  • TP301.6
[1] 武启平,金亚萍,任平,等. 自动导引车(AGV)关键技术现状及其发展趋势[J]. 制造业自动化,2013,35(5):106-109,121.
[2] 杨璐,汪博涵,张雪洁. 基于A*算法的AGV路径规划研究[J]. 公路与汽运,2014(4):47-49.
[3] 泰应鹏,邢科新,林叶贵,等.多AGV路径规划方法研究[J].计算机科学,2017,44(S2):84-87.
[4] RAJOTIA S,SHANKER K,BATRA J L. A semi-dynamic time window constrained routering strategy in an AGV system[J]. International Journal of Production Research,1998,36(1):35-50.
[5] SHAO Shengjun,XIA Zeyang,CHEN Guodong,et al. A new scheme of multiple automated guided vehicle system for collision and deadlock free[C]//2014 4th IEEE International Conference on Information Science and Technology (ICIST). New York:IEEE,2014:606-610.
[6] DIGANI V,SABATTINI L,SECCHI C,et al. Hierarchical traffic control for partially decentralized coordination of multi AGV systems in industrial environments[C]//2014 IEEE International Conference on Robotics and Automation (ICRA). New York:IEEE,2014:6144-6149.
[7] MIYAMOTO T,INOUE K. Random search for dispatch and conflict-free routing problem of capacitated AGV systems[C]//2013 IEEE International Conference on Systems,Man, and Cybernetics (SMC 2013). New York:IEEE, 2013:1611-1615.
[8] 林清岩. 智能交通中车辆最优路径规划策略研究[D].长春:吉林大学,2013.
[9] 孟凡伟. 带时间窗的AGV车辆蜂群调度优化研究[D].大连:大连理工大学,2012.
[10]蓝志坤,蓝志环. 多AGV系统的动态路径规划算法[J]. 公路交通科技,2012,10:121-125.
[11]赵东雄. 多自动导引小车系统(AGVS)路径规划研究[D].武汉:湖北工业大学,2014.
[12]刘二辉,姚锡凡,蓝宏宇,等.基于改进遗传算法的自动导引小车动态路径规划及其实现[J].计算机集成制造系统,2018,24(6):1455-1467.
[13]杨勇生,崔佳羽,梁承姬,等.基于软时间窗的自动化集装箱码头AGV路径规划[J].广西大学学报(自然科学版),2017,42(5):1793-1801.
[14]梁承姬,沈珊珊,胡文辉.基于路段时间窗考虑备选路径的AGV路径规划[J].工程设计学报,2018,25(2):200-208.
[15]韦燚,刘晓东.集装箱自动化码头AGV带时间约束的路径规划研究[J].新型工业化,2016,6(2):41-45.
[16]张坤. 基于AGV的物流中心货物自动运输路径规划的研究[D].广州:华南理工大学,2017.
[1] SHI Ya-bing, HUANG Yu, QIN Xiao, YUAN Chang-an. K-Means Clustering Algorithm Based on a Novel Approach for Improved Initial Seeds [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2013, 31(4): 33-40.
[2] CAO Yong-chun, SHAO Ya-bin, TIAN Shuang-liang, CAI Zheng-qi. A Clustering Method Based on Immune Genetic Algorithm [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2013, 31(3): 59-64.
[3] ZHANG Chao-qun, ZHENG Jian-guo, LI Tao-shen. Effect of Scout Bees on the Performance of Artificial Bee Colony Algorithm [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2013, 31(3): 72-80.
[4] ZHOU Yan-cong, GU Jun-hua, DONG Yong-feng. Converse Binary Anti-collision Algorithm and Hardware Implementation Based on FPGA [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2013, 31(3): 94-99.
[5] HUANG Min, JIN Ting, ZHONG Sheng, MA Yu-chun. Ant Colony Algorithm for Solving Continuous Function Optimization Problem Based on Pheromone Distributive Function [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2013, 31(2): 34-38.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!