The Tabu Search Procedure: An Alternative to the Variable Selection Methods

Abstract

The effectiveness of the Tabu variable selection algorithm, to identify predictor variables related to a criterion variable, is compared with the stepwise variable selection method and the all possible regression approach. Considering results obtained from previous research, Tabu is more successful in identifying relevant variables than the stepwise method, and the adjusted R⊃2 and the Mallow Cp criteria from all possible regression models for certain conditions. Although not completely effective in identifying all variables related to the criterion variable, Tabu is less likely to select variables unrelated to the criterion variable than the alternative methods. We encourage researchers to consider theory, previous research, and professional judgment when selecting the final set of predictors. Limitations of the study as well as the need for further research are also discussed.