多目标约束下绿色柔性车间机器与AGV集成调度优化  

Integrated Scheduling Optimization of Green Flexible Job-Shop Machines and AGVs Problem under Multi-Objective Constraints

作　　者：张天瑞[1] 朱广豪 ZHANG Tianrui;ZHU Guanghao(School of Mechanical Engineering,Shenyang University,Shenyang 110000,China)

机构地区：[1]沈阳大学机械工程学院,沈阳110000

出　　处：《组合机床与自动化加工技术》2025年第3期232-240,共9页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金面上项目(52075088);辽宁省研究生教育教学改革研究资助项目(LNYJG2022490)。

摘　　要：为降低柔性制造车间加工过程和运输过程的综合能耗,建立了绿色柔性作业车间集成调度问题的双目标优化模型。提出了一种改进型多目标樽海鞘群算法求解,该算法基于工序、机器和AGV三层编码并采用反向学习的初始化策略提高初始种群的质量,采用基于快速非支配排序和外部存储库的选择操作结合改进的交叉变异算子进行非支配解集更新,保证非劣解均匀分布;设置了3种领域结构,基于变领域搜索算法作对存储库中非支配解执行变邻域搜索,提高了局部搜索能力。通过测试算例仿真实验和案例应用,证明了所提算法在解决柔性制造车间机器与AGV集成调度多目标优化问题的有效性。To reduce the overall energy consumption in flexible manufacturing workshops during processing and transportation,a dual-objective optimization model for green flexible job shop scheduling has been established.An improved multi-objective ascidian algorithm is proposed,which is based on three-level encoding of processes,machines,and AGVs and utilizes reverse learning for initializing the population to enhance its quality.The algorithm incorporates a selection operation based on fast nondominated sorting and an external archive,along with an improved crossover and mutation operator for updating the nondominated solution set,ensuring a uniform distribution of non-inferior solutions.Three domain structures are defined to execute variable neighborhood search on the nondominated solutions in the archive,enhancing local search capabilities.Through simulation experiments and case studies,the effectiveness of the proposed algorithm in addressing the multi-objective optimization problem of integrating machines and AGVs in flexible manufacturing workshops has been demonstrated.

关 键 词：绿色柔性车间 集成调度 多目标优化 樽海鞘群算法 变领域搜索 

分 类 号：TH165[机械工程—机械制造及自动化] TG659[金属学及工艺—金属切削加工及机床]