Abstract: In a discrete workshop production environment,the degradation process of equipment is influenced by external random shocks,and production planning is affected by equipment conditions. Production planning can be jointly optimized with maintenance scheduling. To address this,a production scheduling optimization model that considers equipment degradation was proposed. To solve this model,a degradation model considering random external shocks was used,with the goal of minimizing the maximum completion time. A Tri-Population Evolutionary Genetic Algorithm (TPEGA) was designed for this purpose. This algorithm employs three distinct populations with different functions to collaboratively search for the optimal solution,restricting the population size while maintaining diversity among high-quality solutions. To avoid falling into local optima,a local optima probability model and an individual discarding strategy were devised. Additionally,to optimize the initial population,a greedy selection strategy considering the equipment with the highest load and process time was proposed. Experimental results demonstrate the effectiveness of the algorithm and the feasibility of the model.

Key words: production scheduling, maintenance scheduling, Tri-Population Evolutionary Genetic Algorithm (TPEGA), equip-ment degradation