why recombination should be adaptive
Crossover is the most complicated of the standard genetic operators as well as one of the main operators in genetic algorithms. The role of the crossover operator has not been satisfactorily explained. It has not been easy to show if it is essential for the construction and exploitation of building blocks during evolution. In this paper we introduce an adaptive crossover operator for two test functions. The results show that there is a clear increase in the rate of evolution when information on the state of the population is used to select the crossover point, compared to random selection of the crossover point.
recombination adaptation genetic algorithm crossover point