Integrated modeling and scheduling for stochastic flexible job shops considering machine degradation and production dynamics

Manufacturing dominates a crucial position in the global economy, driving technological advancement and economic development. In fact, while modern manufacturing has made great strides in efficiency, the production process still faces numerous challenges that create operational uncertainties. In recent years, the Flexible Job Shop Scheduling Problem (FJSP) has emerged as a key approach to addressing these industry issues. However, in practical production processes, random failures caused by machine degradation due to wear and tear should not be underestimated, making the Stochastic Flexible Job Shop Scheduling Problem (SFJSP) more realistic than the FJSP. This study proposes an integrated modeling and scheduling framework for flexible job shops with stochastic machine degradation. The approach combines a serial production line model that captures the dynamics of degrading machines and workpiece order processing across workshops, with an enhanced Artificial Bee Colony algorithm that simultaneously optimizes workshop assignment, makespan and processing costs. By jointly considering machine degradation patterns and production line dynamics, the proposed method demonstrates significant improvements in scheduling performance under complex operational scenarios.