Resolution of overlapping chromatographic peaks using a genetic algorithm

A genetic algorithm for resolution of overlapping chromatographic peaks (GA ROCP) using real-number coding, non-uniform mutation and arithmetical cross over methods is described in this paper. It was applied to resolution of hi ghly overlapped multicomponent high-performance liquid chromatographic peak s by fitting experimental chromatogram to the exponentially modified Gaussi an (EMG) model. The genetic algorithm was used to find the minimum of fitti ng error to optimize the parameters in the EMG functions which determine th e shape and area of each peak. The applicability of the method was investig ated with both simulated signals calculated by EMG functions and experiment al multicomponent overlapping chromatograms.