Optimization strategies peak resolution

Typically, resolution diagrams in MLC are complex, with several local maxima, frequently denoting interaction between factors. For this reason, reliable optimal conditions require considering all factors simultaneously, by applying an interpretive optimization strategy (i.e., based on the description of the retention behavior and peak shape of solutes). In this task, the product of free peak areas or purities has proved to be the best optimization criterion. An interactive computer program is available to obtain the best separation conditions in... 

The prediction of retention data is also quite complicated and the accuracy achievable is not sufficient for the use in optimization by calculations only. One reason is that the handling of retention data is based on diluted samples, but these solutions are far from the ideal solution that is covered by theory. Because only partition coefficients can be predicted, the equation used to calculate the resolution of two peaks can change a 5% error in the partition coefficient to a 100% error for the resolution. This will be discussed in more detail later. Because the prediction of retention data is not satisfactory, optimization is only feasible by a combination of experimental data and an algorithmic optimization strategy. 

---