考虑装配序列变化与双资源约束的模糊柔性装配作业车间调度研究  

Fuzzy flexible assembly job shop scheduling under dual resource constraints considering assembly sequence variation

作　　者：路鑫 鲁聪 LU Xin;LU Cong(School of Mechanical and Electrical Engineering,University of Electronic Science and Technology of China,Chengdu 611731,CHN)

机构地区：[1]电子科技大学机械与电气工程学院,四川成都611731

出　　处：《制造技术与机床》2025年第3期166-179,共14页Manufacturing Technology & Machine Tool

基　　金：四川省科技计划项目(2021YJ0034)。

摘　　要：提出一种考虑装配序列变化与双资源约束的模糊柔性装配作业车间调度(fuzzy flexible assembly job shop scheduling considering assembly sequence variationunder dual resource constraints,FFAJSS-ASVDRC)方法,以实现在双资源约束(包含机器与工人)和操作时间不确定条件下零件加工序列与装配序列的同步优化。通过分析FFAJSS-ASVDRC问题,建立了以最小化总生产完成时间、总库存时间和总花费为目标的数学模型。为合理安排加工与装配工序,分配机器、装配工位和工人,设计了一种3层分段混合染色体结构,提出基于Q-Learning的遗传算法(QLearning based genetic algorithm,QLGA),实现染色体交叉范围的自适应调整,以提高所获取非支配解的质量。通过案例研究,证明了所提出的基于QLGA在求解FFAJSS-ASVDRC时的有效性、优越性和鲁棒性。In this study,a fuzzy flexible assembly job shop scheduling considering assembly sequence variation under dual resource constraints(FFAJSS-ASVDRC)is proposed to optimize the part processing sequence and assembly sequence simultaneously under dual resource constraints,considering the uncertainty of operation time.By analyzing the problem in FFAJSS-ASVDRC,a mathematical model is established aiming to minimize the total production completion time,total inventory time and total cost.Furthermore,in order to assign operation,machine and worker reasonably,a three-layer segmented hybrid chromosome encoding structure is designed.Meanwhile,a Q-Learning based genetic algorithm(QLGA)is proposed to realize the adaptive adjustment of the crossover range of chromosomes to improve the quality of the obtained non-dominated solutions.In the case study,the effectiveness,superiority and robustness of QLGA is verified in solving the FFAJSS-ASVDRC problem.

关 键 词：柔性装配作业车间调度 双资源约束 装配序列 Q-LEARNING NSGA-Ⅱ 

分 类 号：TH165[机械工程—机械制造及自动化]