关键词: 航空构件制造, 柔性作业车间调度, 双资源约束, 数控设备, 教与学算法

Abstract: Aiming at the complex manufacturing environment of aeronautical components flexible job shop,a flexible job shop scheduling problem with Extended Dual Resource Constraints (EDRC) was proposed with considering the constraints such as the wide application of Numerical Control (NC) machine,the interpolation of machining operations/non-machining operations sequence in the process routes and the key processes with cooperation of special machine and labor,and a scheduling model was constructed.A novel multi-group teaching-learning-based optimization was developed to optimization the selection of machine and people for components and the sequence of the operations.Considering the characteristic of no personnel assistance during machine running of NC equipment,a three-layer encoding and a new decoding method were approached to avoid using conflict of machine and people.In addition,various teaching/self-learning factors,self-learning/communication strategies were designed based on the basic core framework of TLBO unchanged to ensure solve discrete problems effectively and balancing the global and local search ability of the algorithm.Experimental results on several random benchmarks and a real scheduling case of aerospace components demonstrated that the proposed algorithm had good performance on EDRC problem and proved the effectiveness of the scheduling model.

Key words: aerospace components production, flexible job shop scheduling, dual resource constraints, numerical control machine, teaching- learning-based optimization