According to Eells, the probabilities evolve as follows.
In the simulation, the NSGA-II has a population size of 50, a crossover probability of 0.4, a mutation probability of 0.1, and evolves for 200 generations.
Crossover and mutation probabilities are 80 and 10%, respectively.
For setting mutation probability, five mutation probabilities: 0, 0.02, 0.03, 0.03, and 0.04, have been applied on five instances.
When mutation probability increased linearly with male age, females generally evolved a preference for younger males and avoided intermediate age males (Fig. 1A).
The steps in GA include reproduction, crossover, and mutation to evolve better solutions.
If the change has no effect, then the mutation will evolve neutrally through genetic drift.
However, SGA may also result in equally good realization, if the algorithm evolves for more number of iterations or optimized values of crossover and mutation probability are used.
A low mutation probability may hinder the production of the new individual, which is not conducive to the worse individual evolving.
Previous models for the evolution of female preference based on male age have showed that in most cases, females will evolve a preference for intermediate-aged and older males and a bias against younger males when mutation probability is constant with age [7], [8], [10].
