As we known, the genetic algorithm is a random procedure, and its results are related to the initial random seed.
From a paper(Lucas. et al., 2015 ), it says "A genetic algorithm can therefore derive a diverse set of Pareto optimal solutions in a single optimization run, which is a great advantage over other methods that require multiple runs to characterize the multiple objective space"
A similar work I have done is also obtained from a single optimization run. And I want to set an repeated experiment to test the robustness of the GA performance.
How to measure the robustness of the genetic algorithm. I have set different seeds and done several repeated experiments.