Further investigation on a comparative study of simulated annealing and genetic algorithm for wavelength selection

A recent publication compared the abilities of simulated annealing (SA), genetic algorithm, and stepwise elimination to determine optimal combinations of wavelengths for quantitative analysis of a chemical system. Using their implementation of SA, the authors were unable to identify the global optimum solution in the experiments they performed with three optimization criteria. However, using a different approach with SA, this paper shows that SA can indeed locate the best solution for the addressed problem and optimization criteria. The importance of wavelength searching in a close neighborhood of the previously evaluated wavelength subset for successful implementation of SA is demonstrated. A procedure is described that identifies optimal wavelength combinations exactly. This paper also addresses the assumed need to determine optimal wavelength combinations and the suitability of the used optimization criteria to establish calibrations with increased prediction accuracy and precision. Some general problems inherent to the standard SA algorithm are discussed.