Improved natural crossover operators in GBIVIL

Aguilar-Ruiz et al proposed crossover operators, both discrete and continuous, for the natural representation (henceforth called NCO). NCO showed advantages in accuracy and in efficiency compared to the binary ones. However, they do not explore the search space like the two points crossover when the binary coding is used. In order to do so, in our previous work we proposed a new natural discrete crossover operator, which gave very good results compared to C4.5 in several UCI databases. Nonetheless, it was not experimentally compared to NCO. So, in this work, we perform this comparison in the same datasets and define a new natural continuous crossover operator, which is also compared to the continuous NCO operator. The experimental results showed the advantages of both new natural operators: our discrete operator achieves better accuracy and simpler concepts using less time, whereas our continuous operator is also able to explore the search space in a more efficient way, leading to better results in less time.