重庆邮电大学学报（自然科学版）2026，Vol.38Issue(1)：74-82,9.DOI:10.3979/j.issn.1673-825X.202411180264
Q学习模因算法求解可重入置换流水车间调度问题
Q-learning memetic algorithm for solving the reentrant flow-shop scheduling problem
摘要
Abstract
The reentrant permutation flow-shop scheduling problem,as a classic NP-hard problem in the field of production scheduling,presents a challenging irregular and large solution space,which poses difficulties for the search of common intelligent optimization algorithms.To tackle this problem,this paper designs a Q-learning-based memetic algorithm that can adaptively select global search operators to minimize the maximum completion time.In the Q-learning-based memetic algorithm,we first design four global search operators tailored to the problem characteristics;second,the integration of the Q-learning mechanism enables the algorithm to adaptively select the most suitable global search operators during the itera-tive process,thereby enhancing the algorithm's efficiency;finally,in the population update phase,we adopt a population update mechanism based on quality and distance,which not only ensures the quality of the solution but also maintains the diversity of the population.Through simulation experiments and comparative experiments with other algorithms,we verify the effectiveness and robustness of the Q-learning-based memetic algorithm proposed in solving the RPFSP problem.关键词
可重入/置换流水车间/模因算法/Q学习/自适应/种群更新Key words
reentrant/flow-shop/memetic algorithm/Q-Learning/adaptive/population update分类
信息技术与安全科学引用本文复制引用
吕卓红,李作成,钱斌,胡蓉..Q学习模因算法求解可重入置换流水车间调度问题[J].重庆邮电大学学报（自然科学版）,2026,38(1):74-82,9.基金项目
国家自然科学基金项目(62173169,61963022) （62173169,61963022）
云南省基础研究重点项目(202201AS070030) （202201AS070030）
云南省高校工业智能与系统重点实验室建设项目(KKPH202403003) National Natural Science Foundation of China(62173169,61963022) （KKPH202403003）
Basic Research Key Project of Yunnan Province(202201AS070030) （202201AS070030）
Construction Project of Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province(KKPH202403003) （KKPH202403003）
