Abstract:

To identify critical to quality characteristics (CTQs) for complex products, a genetic simulated annealing algorithm(GSA)based feature selection algorithm is proposed. As the proposed algorithm combines the genetic algorithm (GA) and simulated annealing algorithm (SA), it has both good local search ability and good global search ability. Additionally, the proposed algorithm adopts an aggregated fitness function, which can optimize the classification performance on CTQ set and the number of selected quality characteristics simultaneously. Experimental results illustrate that the proposed algorithm can efficiently eliminate irrelevant and redundant quality characteristics and identify CTQs, as it can identify fewer CTQs with even higher predictive accuracy compared with the Memetic algorithm and the information gain (IG) algorithm.