摘要
针对柔性作业车间调度在机器故障扰动情况下的动态性及工件交货期模糊的情况,研究采用基于事件与周期混合驱动的滚动窗口再调度策略,并运用线性加权和的方法,以最大完工时间最小、能耗最小、客户满意度最大为目标,建立多目标柔性作业车间动态调度模型,并设计了遗传算法与模拟退火算法结合的GASA算法。将算例仿真结果与遗传算法取得的结果进行对比,验证算法的有效性。
In view of the dynamic characteristics of flexible job shop scheduling under machine fault disturbance and the ambiguity of job delivery time,this paper adopts a rolling window rescheduling strategy driven by event and cycle,and uses the method of linear weighted sum to establish a multiobjective flexible job shop dynamic scheduling model with the objective of minimizing the maximum completion time,minimizing energy consumption and maximizing customer satisfaction.A GASA algorithm combining genetic algorithm with simulated annealing algorithm is designed.The effectiveness of the algorithm is verified by comparing the simulation results with those obtained by genetic algorithm.
作者
曹庆奎
张晓丽
任向阳
CAO Qingkui;ZHANG Xiaoli;REN Xiangyang(Management Engineering and Business School,Hebei University of Engineering,Handan,056038,Hebei,China)
出处
《河北工程大学学报（自然科学版）》
CAS
2019年第2期91-96,共6页
Journal of Hebei University of Engineering:Natural Science Edition
基金
河北省社会科学基金资助项目(HB17GL022)
关键词
柔性作业车间动态调度
遗传算法
模拟退火算法
混合驱动策略
模糊交货期
flexible job shop dynamic scheduling
genetic algorithm
simulated annealing algorithm
hybrid driving strategy
fuzzy delivery date
