Evolutionary algorithm - is there a relation between minimum iterations and size of decision variables I am solving an optimization problem using SPEA2, my problem has three cases with decision variables 25, 50 and 100 in each case. I want to ask if there is some relationship between the number of variables and iterations of evolution process. I mean to say I run algorithm fewer times when decision variables are 25 than once they are 50. Thanks in advance.
As a very general heuristic, it's likely true that bigger problems are harder than smaller ones and benefit from more searching. Bigger populations, longer runs, etc. can be beneficial in that case.

The real question is whether your algorithm is converging or not. If you're converging before you find a good answer, more generations isn't going to help.