
@@ 298,15 +298,16 @@ class ILSPopSurrogate(Algorithm):






self.increaseEvaluation()






+ print(f'=================================================================')



print(f'Best solution found so far: {self.result.fitness}')






# check using specific dynamic criteria based on r^2



r_squared = self._surrogate.analysis.coefficient_of_determination(self._surrogate.surrogate)



mae = self._surrogate.analysis.mae(self._surrogate.surrogate)



training_surrogate_every = int(r_squared * self._ls_train_surrogate)



 print(f"=> R^2 of surrogate is of {r_squared}. Retraining model every {training_surrogate_every} LS")



 print(f"=> MAE of surrogate is of {mae}. Retraining model every {training_surrogate_every} LS")







+ print(f"=> R² of surrogate is of {r_squared}.")



+ print(f"=> MAE of surrogate is of {mae}.")



+ print(f'=> Retraining model every {training_surrogate_every} LS ({self._n_local_search} of {training_surrogate_every})')



# avoid issue when lauching every each local search



if training_surrogate_every <= 0:



training_surrogate_every = 1
