基于效率最大化的RGV动态调度的算法设计与程序验证
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  • 英文篇名:The Algorithmic Design and Program Verification of RGV Dynamic Scheduling Based on the Maximization of Efficiency
  • 作者:周晓玲 ; 李政 ; 李慧东 ; 张卓力 ; 过昱企
  • 英文作者:ZHOU Xiao-ling;LI Zheng;LI Hui-dong;ZHANG Zhuo-li;GUO Yu-qi;School of Mathematical Sciences, Tianjin Polytechnic University;School of Physical Science and Technology, Tianjin Polytechnic University;
  • 关键词:多目标优化模型 ; RGV动态调度规则 ; 作业效率 ; 模型检验
  • 英文关键词:multi-objective optimization model RGV dynamic scheduling rules;;operating efficiency;;model checking
  • 中文刊名:ZQGZ
  • 英文刊名:Management & Technology of SME
  • 机构:天津工业大学数学科学学院;天津工业大学物理科学与技术学院;
  • 出版日期:2019-02-15
  • 出版单位:中小企业管理与科技(中旬刊)
  • 年:2019
  • 期:No.566
  • 语种:中文;
  • 页:ZQGZ201902070
  • 页数:2
  • CN:02
  • ISSN:13-1355/F
  • 分类号:142-143
摘要
论文旨在研究智能RGV(轨道式导引小车)的动态调度策略,针对具体加工过程中的不同情况分别建立以效率最大化为目标的多目标优化模型和实时动态调度策略模型。针对加工情况为两道工序且可能存在故障的情况建立动态调度规则,运用MATLAB软件对动态调度模型进行求解,得到最优调度方案。利用组内检验和组间检验对模型的实用性和算法的有效性进行了检验并评价了模型的优缺点。最后,针对RGA可提前预测CNC完成情况方面对模型进行了合理有效展望。
        The aim of this paper is to study the dynamic scheduling strategy of intelligent RGV(orbit guided vehicle). According to different situation in the concrete manufacturing process, the multi-objective optimization model and the real-time dynamic scheduling strategy model with the goal of efficiency maximization are established respectively. In this paper, a dynamic scheduling rule is established for the case of two processes and possible faults. The dynamic scheduling model is solved by using MATLAB software, and the optimal scheduling scheme is obtained. The practicability of the model and the validity of the algorithm are tested by means of intra-group test and inter-group test, and the advantages and disadvantages of the model are evaluated. Finally, a reasonable and effective prospect is put forward in view of the RGA can predict CNC completion in advance.
引文
【1】乔非,吴启迪. SJ—FMS中RGV的实时调度与故障调度[J].组合机床与自动化加工技术, 1995(3):39-43.
    【2】江唯,何非,童一飞,等.基于混合算法的环形轨道RGV系统调度优化研究[J].计算机工程与应用唯一官方网站, 2016, 52(22):242-247.
    【3】刘永强.基于遗传算法的RGV动态调度研究[D].合肥:合肥工业大学,2017.

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