Flexible Scheduling Optimization in Cigarette Packaging Workshops Based on Genetic Algorithms

The intelligent level of the cigarette - making and packaging workshops in tobacco factories is constantly increasing. However, large - scale tobacco enterprises still face challenges in the arrangement of production processes. This paper focuses on the scheduling problem in cigarette packaging workshops, introduces a genetic algorithm, and constructs a mathematical model with the goal of minimizing the completion time. Tested with the actual production data of a cigarette factory, this algorithm can effectively save time. In a 6×6 scale example, the minimum value of the best maximum completion time is 55 working hours, and it converges around the 40th generation, demonstrating good practical application value.