控制理论与应用2026，Vol.43Issue(4)：865-873,9.DOI:10.7641/CTA.2024.40224
改进教学优化算法求解执行器配置与生产调度协同优化问题
Improved teaching-learning-based optimization algorithm for collaborative optimization of end-effector allocation and production scheduling
摘要
Abstract
In the practical flexible job-shop,the efficient collaboration between end-effector allocation and production scheduling benefits providing global decision-making,thus facilitating the flexibility of the workshop.To address the collaborative optimization problem of end-effector allocation and production scheduling,a mixed-integer programming model is constructed to minimize the comprehensive production cost and makespan,enabling the accurate solution of small-scale problems via Gurobi.In addition,a dual-stage discrete teaching-learning-based optimization algorithm is proposed,incorporating a distance-based adaptive adjustment strategy for learning coefficient and an improved neighborhood search based on critical operation movement to facilitate efficiency and objective balancing.Through simulation experiments,the superiority of the proposed collaborative optimization method and the effectiveness of the proposed algorithm are analyzed and validated.关键词
柔性作业车间调度/资源配置/多目标优化/教学优化算法Key words
flexible job-shop scheduling/resource allocation/multi-objective optimization/teaching-learning-based optimization algorithm引用本文复制引用
谭伟华,吴亮红,李哲,袁小芳..改进教学优化算法求解执行器配置与生产调度协同优化问题[J].控制理论与应用,2026,43(4):865-873,9.基金项目
国家重点研发计划项目(2021YFB3301800),国家自然科学基金项目(62373146),湖南省自然科学基金项目(2022JJ30265),湖南省科技人才托举工程项目(2022TJ-Q03)资助. Supported by the National Key Research and Development Program of China(2021YFB3301800),the National Natural Science Foundation of China(62373146),the Natural Science Foundation of Hunan Province(2022JJ30265)and the Young Talent of Lifting Engineering for Science and Techn-ology in Hunan Province(2022TJ-Q03). （2021YFB3301800）
