Objective function decomposition within genetic algorithm
K.G. Khoo, Ponnuthurai Nagaratnam Suganthan · 2003
The genetic algorithm (GA) has been applied to numerous optimization problems since its introduction. Here, information on each element of the solution strings is extracted to improve the GA's performance. We decouple a fitness evaluation function, estimating the fitness contribution by each dimension. Using this information, each dimension within each solution fights for its position in the offspring. A comparison with the standard GA showed that the proposed GA is superior on commonly tested functions.