I have a GA code that takes a very long time to converge(like 3-4 days), I want to know what is the bestparameter tuning method for it?I simply want to just tune population size, crossover and mutation rate.can I use classical parameter tuning methods such as DOE, EVOP, RSM etc but in a small number of generations and find the best levels of the parameters and then run the algorithm with those levels till convergence. Is it a reasonable method?Also can someone please tell me about 'Racing' method?Thank you in advance for any help.
How is parameter tuning done in real-world problems with very long run times?
genetic algorithms