I created a phylogenetic tree of 328 species using RAxML. I run the ML algorithm 20 times and i chose the best tree (the one with the highest likelihood).
The choice of 20 iterations was based on a tutorial that was carrying out the same analysis but on fewer species.
Now I have a doubt that my search is actually not optimal, and could have got better by increasing the number of iterations.
Do you know if there is a way to estimate the optimal number of iterations to find the best robust ML Tree?

I created a phylogenetic tree of 328 species using RAxML. I run the ML algorithm 20 times and I chose the best tree (the one with the highest likelihood).

The choice of 20 iterations was based on a tutorial that was carrying out the same analysis but on fewer species.

Now I have a doubt that my search is actually not optimal, and could have got better by increasing the number of iterations.

Do you know if there is a way to estimate the optimal number of iterations to find the best robust ML Tree?