轻工机械2024，Vol.42Issue(3)：100-107,8.DOI:10.3969/j.issn.1005-2895.2024.03.015
面向智能生产的分布式流水车间调度研究
Research on Distributed Flow Shop Scheduling for Intelligent Production
摘要
Abstract
In order to make the traditional flow shop scheduling model more flexible and intelligent to adapt to different production environments,scheduling strategy of distributed flow shop based on deep learning was proposed.By learning and analyzing a large amount of data in the distributed shop floor system,the strategy gradient method was used to obtain the approximate optimal solution after several iterations of optimization,and a more intelligent and adaptable production planning and scheduling strategy was obtained.It was verified by experiments and simulation.The results show that this method can improve production efficiency and resource utilization,and has potential in cost control.The research provides an advanced scheduling strategy for distributed production environment of manufactur industry,and provides more accurate and intelligent decision reference for shop floor managers.关键词
生产调度/分布式流水车间/深度学习/调度策略/策略梯度法Key words
production scheduling/distributed flow shop/deep learning/scheduling strategy/strategy gradient method分类
通用工业技术引用本文复制引用
陈俊贤,李仁旺..面向智能生产的分布式流水车间调度研究[J].轻工机械,2024,42(3):100-107,8.基金项目
浙江省2023年度"尖兵""领雁"研发攻关计划(2022C01SA111123) （2022C01SA111123）
国家自然科学基金资助项目(51475434). （51475434）
