遗传算法在配方优化中的应用

Application on Genetic Algorithms in Optimization of Formula

卷烟配方优化的主要任务是根据设计目标,有约束地优化求解,得到多组最佳或次佳烟叶组合比例。本文利用遗传算法,以烟叶理化成份与卷烟感官、烟气指标相关性为依据,确定约束条件设计优化模型以达到最低成本为目标,通过优化模型的运行来取得所需风格卷烟的最佳配比组合,同时能提前对设计出的叶组配方进行预估,实现对重点指标的重点控制,使设计更具科学性和合理性。

In optimization of cigarette formulating the main task is how to optimize the restricted cigarette formulating problem. The thesis takes advantage of genetic algorithms, based on the relevance of tobacco leaf physical and chemical composition with cigarette sensory and flue gas index, identify constraints design optimization model to achieve the goal of the lowest cost. By operating the optimized model, can obtain the required cigarettes style with best ratio combinations. At the same time, it can estimate the designed cigarette blending formulation ahead of time. To realize the key control to the key target, and make the design more science and rationality.