Repairing the crossover rate in adaptive differential evolution ?
The behavior of the crossover in differential evolution (DE) is analyzed. A crossover rate repair technique for the adaptive DE algorithm is proposed. The crossover rate in DE is repaired by its corresponding binary string, i.e. by using the average number of components taken from the mutant. Experimental results indicate that our proposed crossover rate technique is able to enhance the performance of JADE.
differential evolution crossover rate repair binary string parameter adaptation numerical optimization