In this example the optimizer is used to optimize another optimizer.
The fitness function takes as input 3 parameters with which it will launch 100 searches on the Rastrigin function and return the average mean fitness after 10 iterations.
The meta-optimizer will try to find the parameters for which the optimizer will return the best results.
Parameter values for best simulation found, by iteration
Inertia weight
Social influence
Personal influence
Average of the average values found in the whole population
Average of the best solution found during each iteration