遗传算法用于液相色谱分离条件的优化

Application of Genetic Algorithm in Optimization of Mobile Phase Composition in High Performance Liquid Chromatography

在参考传统的优化方法的基础上 ,将遗传算法用于等度反相色谱多元流动相分离条件的优化。详细介绍了基于线杂交和面变异的遗传算法的原理及其用于液相色谱分离条件优化的过程。将此法用于 9种小肽的反相离子对色谱分离条件的优化 ,经过 3次寻优操作 ,确定了最佳分离条件 ,实验保留值与预测值的平均相对偏差为0 75 % ,优化结果比较理想。

Referring to traditional optimal methods, a method for the optimization of isocratic elution mobile phase composition in high performance liquid chromatography has been developed. In this method, the genetic algorithm based on line-crossover and plane-mutation is used. The principle of genetic algorithm and the process of optimization of mobile phase composition in reversed-phase ion-pair high performance liquid chromatography using genetic algorithm are introduced in details. With the concentrations of acetonitrile and ion-pair reagent sodium octane sulfonate chosen as the optimal parameters, the optimum was obtained by three times of optimization procedures. The mean relative error between the predicted and experimental values was 0.75% at the optimum and the optimization results were satisfactory.