How to choose optimizer
The default choice of optimization methods in params_file is the following:
Genetic_algorithm as
Global optimizer,BFGS_log as
Local optimizer.
We recommend to use BFGS_log as local search algorithm. Genetic_algorithm is also the most efficient method for demographic inference with GADMA.
However, there are special cases when it is better to use Bayesian optimization as a global search algorithm. Usually it is case for demographic inference with more than three populations. More about Bayesian optimization could be found here.
Below there is a table with recomendations about global search algorithm choice. GA stands for the genetic algorithm, BO for Bayesian optimization. Symbol ? means that we have not checked the efficiency for Bayesian optimization in that settings.
Pop.num.Engine |
|
|
|
|
|---|---|---|---|---|
1 |
GA |
GA |
GA |
GA |
2 |
GA |
GA |
GA |
GA |
3 |
GA or BO * |
GA |
GA |
? |
4 |
BO |
BO |
GA |
? |
5 |
BO |
BO |
GA |
? |
>5 |
✖ ** |
✖ ** |
GA |
✖ ** |
* depends on the time of log-likelihood evaluation. If grid size (Pts) or sample size of data are big then BO is better choice, otherwise GA should be used.
** Not supported