We have been having unexpected results in our optimization processes, using the genetic algorithm. We have found that the diversity of the population seems to increase back to the original population diversity at the beginning of the optimization process.
This appears to happen in mostly periodic steps in the generation every n generations. What seems odd is that the population immediately then collapses back to the diversity it had before the diversification.
We have had more than one script, by different users, produce the same result. We understand that the GA should change the diversity overtime, but it does not seem that the diversity should ‘explode’ for a single iteration, followed by an ‘implosion’ the next iteration.
This is demonstrated in the figure below showing the generation at a specific generation.
We are trying to optimize three integer variables with only upper and lower bounds on the variables, there is no constraints. The optimization is finding the a near optimal solution, but we want to understand why this population is diversifying periodically as a function of generation.
The same behavior is seen for different max generation counts also. Yet the period seems to change given the max generation count.
We observe the same behavior regardless of our fitness function, as can be seen below.
We have tried to change the crossover, scale and other settings, we can minimize this, but it still appears to happen. Again, it’s not so much that the population is becoming diverse, it’s the change of the magnitude of diversity over time that is our concern.
Thank you!
