Synchronized optimization of the logistics system of a tobacco high-bay warehouse under production task fluctuations

Abstract Cigarette companies often utilize a logistics system where high-bay warehouse areas for semi-finished and finished tobacco products are located close together and linked via trolley tracks. However, fluctuations in production tasks, such as adding new tasks, handling emergency orders, and canceling existing orders, can introduce challenges to production, including high storage capacity ratios and limited trolley transportation capacity. Therefore, this study proposes a synchronized optimization method for the logistics system in tobacco high-bay warehouses designed to improve storage and transportation efficiency. A synchronized storage allocation model is developed to balance the capacity ratios between the two high-bay warehouses to tackle high storage capacity ratios. The efficiency is improved by minimizing stacker handling time and optimizing shelf center of gravity, with the warehouses’ capacity ratios serving as key constraints. A neural network model is introduced to enhance trolley transportation capacity by predicting the optimal number of trolleys needed for each functional area based on task volume, boosting overall transportation efficiency. Experimental analysis demonstrates that the proposed coordinated operation method enhances high-bay warehouse storage efficiency by 36.82% and transportation efficiency by 8%. This study achieves synchronized optimization of the logistics system in cigarette enterprises by designing a shared coordination scheme for storage locations and trolleys. Lastly, this study effectively supports the tobacco industry in addressing dynamic production demands and provides valuable insights for practical engineering applications.