Dynamic Stability-Aware Scheduling based on Dueling Double Deep Q-Network in FJSP
Jiarong Du, Fangyu Li, Honggui Han · 2024
The growing complexity of the industrial production environment introduces various uncertain events, resulting in increased process instability and reduced production efficiency. The stable scheduling method is crucial to ensure the continuous and stable operation of the production process. However, the existing dynamic flexible job shop scheduling problem (DFJSP) research lacks stability analysis of the scheduling method. To optimize the production process, we propose a dynamic stability-aware scheduling method based on dueling double deep Q-network (DSAS-D3QN). The method solves DFJSP with multiple uncertain events and reduces the job processing time. Meanwhile, we analyze the stability of the scheduling method by describing the overall distribution of DSAS-D3QN’s reward function values. The experiment shows that the proposed method can effectively reduce the processing time while ensuring the stability of the scheduling. Through stability analysis, we verify the adaptability of DSAS-D3QN to unstable environmental changes.