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We describe the decomposition of QSO absorption line ensembles applying anevolutionary forward modelling technique. The modelling is optimized using anevolution strategy (ES) based on a novel concept of completely derandomizedself-adaption. The algorithm is described in detail. Its global optimizationperformance in decomposing a series of simulated test spectra is compared tothat of classical deterministic algorithms. Our comparison demonstrates thatthe ES is a highly competitive algorithm capable to calculate the optimaldecomposition without requiring any particular initialization.

Evolution strategies applied to the problem of line profile decomposition in QSO spectra