工业工程2025，Vol.28Issue(2)：58-68,11.DOI:10.3969/j.issn.1007-7375.240125
考虑订单交货期的柔性作业车间主动调度方法
An Active Scheduling Method for Flexible Job Shops Considering Order Delivery Deadlines
摘要
Abstract
With the rapid development of the Internet of Things technology and industrial infrastructure,the digitalization and networking of manufacturing sites are continuously improving,providing technical foundation and guarantee for intelligent scheduling and control of production tasks in discrete manufacturing job shops.At present,the growing demand for multi-variety,small-batch,and customized products is making the workshop environment increasingly complex and variable,thereby amplifying the uncertainty of order delivery deadlines.However,the remaining completion time of orders is a key factor affecting delivery deadlines.Based on the strong data perception and acquisition ability of shop sites,an active scheduling method for flexible job shops considering order delivery deadlines is proposed.Firstly,a scheduling decision model based on an improved deep Q-network is established,where the predicted remaining completion time of orders is incorporated as one of the state features of the decision-making model to enhance the proactivity of scheduling.A composite scheduling rule action set is designed for the problem of job assignment to machines and job selection in machine buffers.The optimization objectives are to minimize the maximum completion time,total delay time,and average delay time.The decision-making model is trained to select the optimal action according to the real-time data through the prediction network and the target network,so as to realize active scheduling of the production process while ensuring multi-objective global optimization.Finally,the effectiveness and superiority of the proposed scheduling method are verified by application.关键词
订单交货期/柔性作业/主动调度/改进深度Q网络Key words
order delivery deadlines/flexible operation/active scheduling/improved deep Q-network分类
信息技术与安全科学引用本文复制引用
朱海华,陶帅,王健杰,张毅,唐敦兵,刘长春..考虑订单交货期的柔性作业车间主动调度方法[J].工业工程,2025,28(2):58-68,11.基金项目
国家自然科学基金资助项目(92267109) （92267109）
江苏高校"青蓝工程"资助项目 （）
江苏省卓越博士后计划资助项目(2024ZB194) （2024ZB194）
中国博士后科学基金资助项目(2024M754122) （2024M754122）
