Two-stage multiprocessor flow shop scheduling with deteriorating maintenance in cleaner production

Cleaner production has become popular since the global warming problem resulted from most industrial activities. This study proposes an environment of two-stage multiprocessor flow shop scheduling, which allows multiple identical parallel machines in each station, thus enhancing efficiency and resulting in cleaner production. The considerable research interest in the topic of parallel machines suggests that these machines may be highly efficient and effective. Appropriately scheduling deteriorating maintenance activity on parallel machines is necessary to prevent excessive energy consumption and minimize makespan, which is necessary for clean production. Improved processes in the development and use of deteriorating maintenance procedures lead to improved efficiency. Computational results indicate that the proposed method outperforms ant colony optimization and particle swarm optimization with respect to the effectiveness and robustness of clean production. Saving energy can prevent excessive waste. This study demonstrated that the scheduling problem on parallel machines with deteriorating maintenance activity can be solved efficiently in an environment-friendly and economical manner.