Parallel model of independent component analysis constrained by reference curves for HPLC-DAD and its solution by multi-areas genetic algorithm

In order to separate a 3D chromatography, which is generated from High Performance Liquid Chromatography-Diode Array Detector (HPLC-DAD), into chromatograms and spectra, we proposed a model called parallel Independent Component Analysis constrained by Reference Curve (pICARC), which transforms the separation problem to a multi-parameter optimization issue. Then, A new algorithm named multi-areas Genetic Algorithm (mGA) is developed to search multiple solutions in parallel. It was demonstrated that our approach could successfully separate a given HPLC-DAD dataset into chromatograms and spectra with little errors and in short computational time.