沈阳航空航天大学学报2025，Vol.42Issue(3)：65-74,81,11.DOI:10.3969/j.issn.2095-1248.2025.03.009
基于DRQN的复杂产品工艺路线柔性规划方法
A DRQN-based flexible process route planning method for complex products
摘要
Abstract
To address the process route planning problem characterized by dynamic process requirements and intricate process data,a flexible process route planning method was proposed based on deep recurrent q-network(DRQN).Firstly,leveraging the structural advantages of the long short-term memory(LSTM)network,sequential data features were thoroughly mined to enhance the accuracy and stability of process route planning.Secondly,by integrating the robust dynamic decision-making capability of the deep q-network(DQN)with an adaptive adjustment strategy,the challenges posed by fluctuations in requirements and processing environments were effectively mitigated.Lastly,in response to frequent process changes,a"selective forgetting"mechanism was implemented to improve the response speed of process route planning during step process changes.Simulation results demonstrate that the proposed method can efficiently resolve the process route planning issue associated with part occurrence feature reconstruction.关键词
复杂产品/深度强化学习/工艺路线/柔性规划/DRQNKey words
complex products/reinforcement learning/process route/flexible planning/DRQN分类
航空航天引用本文复制引用
李继运,李璐瑜,郭娜,安云哲,夏秀峰..基于DRQN的复杂产品工艺路线柔性规划方法[J].沈阳航空航天大学学报,2025,42(3):65-74,81,11.基金项目
国家自然科学基金(项目编号:62472293). （项目编号:62472293）
