数字平库优化算法的打叶复烤均质化组配模式研究OA

[Background]The outbound material preparation strategy for redrying digital flat warehouses is relatively simple,resulting in insufficient quality stability among batches.[Methods]Based on the flat-warehouse storage mode using small nicotine-content intervals,simulated annealing algorithm and improved genetic algorithm were adopted for outbound blending,and the homogenization effects of traditional material preparation and algorithm-optimized material preparation were compared.[Results]Simulated annealing algorithm can ensure that the mean nicotine content of each outbound unit is basically consistent with that of the overall materials.The improved genetic algorithm evenly divides the outbound units into multiple batches and strictly ensures the stability of the grade proportion within each batch and the nicotine content among batches.Compared with the traditional material preparation method of"interval proportioning+random outbound delivery",the material preparation method based on optimization algorithms shows a significant effect.The nicotine CV value of finished strips decreased from 4.494%to 2.497%,a decrease of 44.437%.[Conclusion]This method provides a feasible and efficient solution for homogenized blending under the flat-warehouse storage mode and has good practical application value.