Wavelength selection with Tabu Search

This paper introduces Tabu Search in analytical chemistry by applying it to wavelength selection. Tabu Search is a deterministic global optimization technique loosely based on concepts from artificial intelligence. Wavelength selection is a method which can be used for improving the quality of calibration models. Tabu Search uses basic, problem‐specific operators to explore a search space, and memory to keep track of parts already visited. Several implementational aspects of wavelength selection with Tabu Search will be discussed. Two ways of memorizing the search space are investigated: storing the actual solutions and storing the steps necessary to create them. Parameters associated with Tabu Search are configured with a Plackett–Burman design. In addition, two extension schemes for Tabu Search, intensification and diversification, have been implemented and are applied with good results. Eventually, two implementations of wavelength selection with Tabu Search are tested, one which searches for a solution with a constant number of wavelengths and one with a variable number of wavelengths. Both implementations are compared with results obtained by wavelength selection methods based on simulated annealing (SA) and genetic algorithms (GAs). It is demonstrated with three real‐world data sets that Tabu Search performs equally well as and can be a valuable alternative to SA and GAs. The improvements in predictive abilities increased by a factor of 20 for data set 1 and by a factor of 2 for data sets 2 and 3. In addition, when the number of wavelengths in a solution is variable, measurements on the coverage of the search space show that the coverage is usually higher for Tabu Search compared with SA and GAs. Copyright © 2003 John Wiley & Sons, Ltd.