GENETIC ALGORITHMS IN WAVELENGTH SELECTION - A COMPARATIVE-STUDY

This paper presents a comparative study involving a genetic algorithm, simulated annealing, and stepwise elimination, as methods for wavelen gth selection in multi-component analysis. The wavelength selection cr iteria used are the selectivity and accuracy after Lorber, and the min imal mean squared error after Sasaki. The genetic algorithm generally performed best. Stepwise elimination performed surprisingly good despi te its local search heuristic. Simulated annealing performed worst, wh ich is remarkable in view of the fact that this method is widely prais ed in the literature for properties similar to those of genetic algori thms, e.g., a probabilistic, non-local search heuristic.