Adaptive genetic operators
Vladimir Estivill‐Castro · 2002
Many intelligent systems search concept spaces that are explicitly or implicitly predefined by the choice of knowledge representation that in effect, serves as a strong bias. Biases heuristically direct search towards favored regions in the search space. The effectiveness of the genetic algorithm depends heavily on the synergy of the crossover operators and selected representation. We discuss the robustness of recombination operators for genetic operators and propose a new family of crossover operators. Experimental results indicate that these new operators strike a superior balance between exploration and exploitation. We provide an analysis that sheds some light on why the new genetic operators are more effective.