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update of output log LS

Jérôme BUISINE il y a 3 ans
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commit
12d9e41a0e
1 fichiers modifiés avec 4 ajouts et 3 suppressions
  1. 4 3
      optimization/ILSPopSurrogate.py

+ 4 - 3
optimization/ILSPopSurrogate.py

@@ -298,15 +298,16 @@ class ILSPopSurrogate(Algorithm):
                     
                     
                 self.increaseEvaluation()
                 self.increaseEvaluation()
 
 
+                print(f'=================================================================')
                 print(f'Best solution found so far: {self.result.fitness}')
                 print(f'Best solution found so far: {self.result.fitness}')
 
 
                 # check using specific dynamic criteria based on r^2
                 # check using specific dynamic criteria based on r^2
                 r_squared = self._surrogate.analysis.coefficient_of_determination(self._surrogate.surrogate)
                 r_squared = self._surrogate.analysis.coefficient_of_determination(self._surrogate.surrogate)
                 mae = self._surrogate.analysis.mae(self._surrogate.surrogate)
                 mae = self._surrogate.analysis.mae(self._surrogate.surrogate)
                 training_surrogate_every = int(r_squared * self._ls_train_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
                 # avoid issue when lauching every each local search
                 if training_surrogate_every <= 0:
                 if training_surrogate_every <= 0:
                     training_surrogate_every = 1
                     training_surrogate_every = 1