考虑能耗的分布式柔性作业车间调度问题研究  

Study of distributed flexible job shop scheduling problem considering energy consumption

作　　者：李岳威 宋李俊 LI Yuewei;SONG Lijun(College of Mechanical Engineering,Chongqing University of Technology,Chongqing 400054,CHN)

机构地区：[1]重庆理工大学机械工程学院,重庆400054

出　　处：《制造技术与机床》2025年第3期157-165,共9页Manufacturing Technology & Machine Tool

基　　金：重庆市自然科学基金项目“时序约束下云制造资源协同服务链构建及优化方法研究”(cstc2020jcyj-msxmX0400)。

摘　　要：针对分布式装配车间的柔性作业车间调度问题(distributed assembly flexible job-shop scheduling problem,DAFJSP),构建了以最小化最大完工时间、车间能耗和机器总负载为优化目标的DAFJSP数学模型。为求解DAFJSP模型,提出了一种改进的启发式算法(improving gold rushing optimization algorithm,IGROA),该算法以改进的淘金算法为全局搜索组件,多种领域搜索算子为局部搜索组件。首先,设计3种领域搜索算子,对Pareto前沿个体进行领域搜索,提高了种群的多样性与收敛速度;其次,在种群选择中提出一种结合模拟退火算法的竞标赛选择方式,提高了全局寻优能力;最后,基于Kacem、MK等算例进行算法验证,证明了算法的优越性。For the distributed assembly flexible job-shop scheduling problem(DAFJSP),a DAFJSP mathematical model is constructed with the minimization of the maximum completion time,the integrated energy consumption of the shop production,and the machine load as the optimization objectives.In order to solve the DAFJSP model,an improving gold rushing optimization algorithm(IGROA)is proposed,which takes the improved gold rush optimizer as the global search component,and a variety of domain search operators as the local search components.Firstly,three domain search operators are designed to improve the diversity and convergence speed of the population by performing domain search on Pareto frontier individuals.Secondly,a bid race selection method combined with simulated annealing algorithm is proposed in the population selection to improve the global optimization search capability.Finally,the algorithm is validated based on Kacem and MK algorithms,which proves the superiority of the algorithm.

关 键 词：淘金算法 邻域搜索算子 分布式装配柔性作业车间调度 多目标优化 能耗 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]