  One of the problems in applying Genetic Algorithm is that there is some
situation where the evolutionary process converges too fast to a solution which
causes it to be trapped in local optima. To overcome this problem, a proper
diversity in the candidate solutions must be determined. Most existing
diversity-maintenance mechanisms require a problem specific knowledge to setup
parameters properly. This work proposes a method to control diversity of the
population without explicit parameter setting. A self-adaptation mechanism is
proposed based on the competition of preference characteristic in mating. It
can adapt the population toward proper diversity for the problems. The
experiments are carried out to measure the effectiveness of the proposed method
based on nine well-known test problems. The performance of the adaptive method
is comparable to traditional Genetic Algorithm with the best parameter setting.
