智能RGV-CNC动态调度问题研究  

Research of Dynamic Scheduling Based on RGV-CNC

作　　者：史爱武[1] 李林峰[1] 薛少杰 邵镔彬 SHI Aiwu;LI Linfeng;XUE Shaojie;SHAO Binbin(Wuhan Textile University,Wuhan 430200)

机构地区：[1]武汉纺织大学,武汉430200

出　　处：《计算机与数字工程》2021年第4期760-765,803,共7页Computer & Digital Engineering

摘　　要：在CNC(Computerized Numerical Control)计算机数控技术下,有轨制导车辆系统在不同的情况下如何高效地调度RGV(Rail Guided Vehicle)穿梭车的问题。按照实际的业务需求,模拟出四种情况,以每项任务所需要的时间作为评判标准,不断地在所有需求信号中选择完成最快的任务去执行,利用贪心算法的原理,通过不断寻找局部最优解,企图获得全局最优解。相较于目前国内研究该问题的解决方案,该方法在实际应用的不但易于实现,而且适应不同的环境要求,运行速度快且极大地提高了作业效率。在实验中得出的仿真结果在不同的情况下平均能达到理想最优解的90%以上。Under the CNC(Computerized Numerical Control)computer technology,the rail-guided vehicle system can effi⁃ciently dispatch the RGV(Rail Guided Vehicle)shuttle in different situations.In accordance with the actual business needs,four situations are simulated,the time required for each task is used as the criterion,the fastest task is continuously selected to execute in all the demand signals,and the principle of greedy algorithm is used to continuously search for local optimal solution attempts to obtain the global optimal solution.Compared with the current domestic research solution to this problem,the method is not only easy to implement in practical application,but also adapts to different environmental requirements,and the running speed is fast and the working efficiency is greatly improved.The simulation results obtained in the experiment can reach more than 90%of the ideal opti⁃mal solution under different conditions.

关 键 词：贪心算法 RGV-CNC动态调度模型 穷举法 CNC数量及位置分配模型 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]