Evolutionary Algorithms for Optimization of Tobacco Leaf Groups Blending

Traditional methods using for the design of tobacco leaf groups blending depend mostly on expert experiences. But they are lack control of the product quality and proved inefficient in practice. In this paper, we use the modified GA and PSO algorithms to help to optimize the leaf groups. The experimental results demonstrated that the modified GA and PSO algorithms are faster and more accurate when compared with the traditional methods; meanwhile PSO performs better than GA in General conditions.