考虑工人约束的分布式柔性作业车间调度问题研究  

Research on Distributed Flexible Job Shop Scheduling Problem Considering Worker Constraints

作　　者：闫炳龙 叶春明[1] YAN Binglong;YE Chunming(School of Business,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《组合机床与自动化加工技术》2025年第4期188-194,共7页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：上海市哲学社会科学一般项目(2022BGL010)。

摘　　要：针对带有工人约束的分布式柔性作业车间调度问题(DFJSPWC),构建了以最小化最大完工时间和最小化总能耗为优化目标的调度模型,并提出了一种改进文化基因算法进行求解。根据问题特点,该算法综合考虑工厂选择、工序排序、机器选择和工人分配4个子问题,采用了四层编码方式,并采用紧前左移插入解码方法提高算法的收敛速度;针对传统文化基因算法容易陷入局部最优的问题,设计了一种自适应局部搜索方法和精英分层保留策略,丰富种群的多样性并增强算法的局部寻优能力;最后,将所提算法与其他算法进行对比,结果表明该算法在求解所提问题时具有显著优势。For the distributed flexible job-shop scheduling problem with worker constraints(DFJSPWC),a scheduling model is constructed with the objectives of minimizing the maximum completion time and minimizing total energy consumption.An improved memetic algorithm is proposed to solve this problem.Considering the characteristics of the problem,the algorithm integrates factory selection,operation sequencing,machine selection,and worker allocation into a four-layer encoding method,and adopts a left-shift insertion decoding method to accelerate the convergence of the algorithm.To address the issue of traditional cultural genetic algorithms getting stuck in local optima,an adaptive local search method and an elite stratification retention strategy are designed to enrich the population diversity and enhance the local search capability of the algorithm.Finally,the proposed algorithm is compared with other algorithms,and the results show that it has significant advantages in solving the problem addressed in the paper.

关 键 词：工人约束 分布式柔性作业车间 改进文化基因算法 自适应局部搜索 

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]