带忽略工序的多目标批量流混合流水车间调度  

Multi-objective lot streaming hybrid flowshop scheduling with missing operations

作　　者：李浩平 朱成彪 陈心怡 彭巍 孟荣华 金朱鸿 杜昕毅 蔡浏阳 LI Haoping;ZHU Chengbiao;CHEN Xinyi;PENG Wei;MENG Ronghua;JIN Zhuhong;DU Xinyi;CAI Liuyang(College of Mechanical and Power Engineering,Three Gorges University,Yichang 443000,China)

机构地区：[1]三峡大学机械与动力学院,湖北宜昌443000

出　　处：《计算机集成制造系统》2025年第1期89-101,共13页Computer Integrated Manufacturing Systems

基　　金：国家重点研发计划资助项目(2018YFB1700801);湖北省水电工程施工与管理重点实验室(三峡大学)开放基金资助项目(2020KSD15)。

摘　　要：针对带忽略工序的批量流混合流水车间调度问题,在考虑批次切换调整时间的情况下,以最小化完工时间和机床负荷平衡为优化目标,建立柔性批量分割和调度集成优化模型,提出一种双层改进PSO-GA混合算法。算法提出批量和机器的双层搜索求解框架,外层进行柔性分批,内层搜索排序及调度方案。针对批量分割、工件批排序、机器分配3个问题,设计基于批量、工序和机器的三段式编码,内层将狼群算法的分级和游走策略引入粒子群算法,设计了一种基于PBX(Position-based Crossover)交叉操作的围攻策略以提高算法的局部搜索及寻优能力。通过仿真实验并与几种启发式算法进行对比及实例验证,说明了调度模型和算法的可行性和优越性。For the lot streaming hybrid flowshop scheduling problem with missing operation,considering the adjustment time by batch changing,a integrated optimization model of flexible batch and scheduling was established by taking the minimize makepan and machine load balance as the optimization objectives,and a double-layer Particle Swarm optimization—Genetic Algorithm(PSO-GA)hybrid algorithm was proposed.The algorithm proposed the double-layer search solution frame for batch and machine,the outer layer carried out flexible batch and the inner layer searched the sorting and scheduling.Aiming at three problems:batch,lot sorting and machine assignment,the three-stage code based on batch,process and machine was designed.The inner layer introduced the grading and wandering strategy of the Grey Wolf Optimizer(GWO)into the PSO.A siege strategy based on Position based Crossover(PBX)cross operation was designed to improve the local search and optimization ability.Through simulation experiments、comparison with several heuristic algorithms and example verification,the feasibility and superiority of the scheduling model and algorithm were verified.

关 键 词：批量流 混合流水车间调度 忽略工序 改进PSO-GA混合算法 双层搜索框架 柔性分批 

分 类 号：TH186[机械工程—机械制造及自动化] TP18[自动化与计算机技术—控制理论与控制工程]