Lund University, Department of Chemical Engineering, Lund, Sweden.
J Chromatogr A. 2011 Dec 23;1218(51):9155-61. doi: 10.1016/j.chroma.2011.10.062. Epub 2011 Oct 28.
This work presents a method to optimize multi-product chromatographic systems with multiple objective functions. The system studied is a neodymium, samarium, europium, gadolinium mixture separated in an ion exchange chromatography step. A homogeneous Langmuir Mobile Phase Modified model is calibrated to fit the experiments, and then used to perform the optimization task. For the optimization a multi-objective Differential Evolution algorithm was used, with weighting based on relative value of the components to find optimal operation points along the Pareto front. The objectives of the Pareto front are weighted productivity and weighted yield with purity as an equality constraint. A prioritizing scheme based on relative values is applied for determining the pooling order. A simple rule of thumb for pooling strategy selection is presented. The multi-objective optimization gives a Pareto front which shows the rule of thumb, as a gap in one of the objective functions.
本工作提出了一种优化具有多个目标函数的多产品色谱系统的方法。研究的系统是在离子交换色谱步骤中分离的钕、钐、铕、钆混合物。将均匀的朗缪尔流动相修正模型进行校准以拟合实验，然后用于执行优化任务。对于优化，使用了基于各组分相对值的多目标差分进化算法，以找到沿 Pareto 前沿的最佳操作点。Pareto 前沿的目标是加权生产力和加权产量，以纯度为等式约束。应用基于相对值的优先级方案来确定合并顺序。提出了一种简单的经验法则用于合并策略选择。多目标优化给出了 Pareto 前沿，其中显示了经验法则，即目标函数之一的差距。
