基于GWO的多目标柔性作业车间动态调度研究  

Research on multi-objective flexible job-shop dynamic scheduling based on GWO

作　　者：姜飞 李国昊[1] 陶斯安 Jiang Fei;Li Guohao;Tao Si'an(School of Management, Jiangsu University, Jiangsu Zhenjiang, 212013,China)

机构地区：[1]江苏大学管理学院,江苏镇江212013

出　　处：《机械设计与制造工程》2022年第5期90-94,共5页Machine Design and Manufacturing Engineering

摘　　要：针对模糊柔性作业车间动态调度问题,在交货期模糊的前提下,首先假设动态干扰事件为机器故障,采用字典序多目标规划方法,以最大完工时间最小与客户满意度总和最大为目标,建立柔性作业车间动态调度模型;然后从改变收敛因子和领导狼权重动态变化两个方面改进灰狼优化算法,使得改进算法的收敛效果和寻优精度较传统灰狼算法有了显著的提升;最后对DS亚克力板材厂的生产数据进行分析,在验证模型和算法可行性的同时,找出了该企业生产的关键设备,为提高企业生产效率和稳定性提供了新的方法和思路。Aiming at the dynamic scheduling problem of fuzzy flexible job shop,under the premise of fuzzy delivery date,firstly assuming that the dynamic disturbance event is a machine failure,the lexicographical multi-objective programming method is adopted,and the goal is to minimize the maximum completion time and maximize the sum of customer satisfaction.The flexible job shop dynamic scheduling model;then,the gray wolf algorithm is improved from the two aspects of changing the convergence factor and the dynamic change of the leader wolf weight,so that the convergence effect and optimization accuracy of the improved algorithm are significantly improved compared with the traditional gray wolf algorithm;finally,the DS production data of the acrylic sheet factory is analyzed,and while the feasibility of the model and algorithm is verified,the key equipment produced by the enterprise is found,which provides new methods and ideas for improving the production efficiency and stability of the enterprise.

关 键 词：柔性作业车间调度 动态调度 灰狼算法 模糊交货期 多目标优化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TH165[自动化与计算机技术—控制科学与工程]