### Update LS no surrogate algorithm

Jérôme BUISINE 4 months ago
parent
commit
9ea9561227
1 changed files with 22 additions and 22 deletions
1. 22 22
optimization/ILSPopNoSurrogate.py

#### + 22 - 22 optimization/ILSPopNoSurrogate.py View File

 ``@@ -317,39 +317,39 @@ class ILSPopSurrogate(Algorithm):`` `` 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"=> R² of surrogate is of {r_squared}.")`` ``- print(f"=> MAE of surrogate is of {mae}.")`` ``+ # # 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"=> R² of surrogate is of {r_squared}.")`` ``+ # print(f"=> MAE of surrogate is of {mae}.")`` `` `` ``- # avoid issue when lauching every each local search`` ``- if training_surrogate_every <= 0:`` ``- training_surrogate_every = 1`` ``+ # # avoid issue when lauching every each local search`` ``+ # if training_surrogate_every <= 0:`` ``+ # training_surrogate_every = 1`` `` `` ``- print(f'=> Retraining model every {training_surrogate_every} LS ({self._ls_local_search % training_surrogate_every} of {training_surrogate_every})')`` ``+ # print(f'=> Retraining model every {training_surrogate_every} LS ({self._ls_local_search % training_surrogate_every} of {training_surrogate_every})')`` `` `` `` `` `` # increase number of local search done`` `` self._n_local_search += 1`` ``- self._ls_local_search += 1`` ``+ # self._ls_local_search += 1`` `` `` ``- # check if necessary or not to train again surrogate`` ``- if self._ls_local_search % training_surrogate_every == 0 and self._start_train_surrogate <= self.getGlobalEvaluation():`` ``+ # # check if necessary or not to train again surrogate`` ``+ # if self._ls_local_search % training_surrogate_every == 0 and self._start_train_surrogate <= self.getGlobalEvaluation():`` `` `` ``- # train again surrogate on real evaluated solutions file`` ``- start_training = time.time()`` ``- self.train_surrogate()`` ``- training_time = time.time() - start_training`` ``+ # # train again surrogate on real evaluated solutions file`` ``+ # start_training = time.time()`` ``+ # self.train_surrogate()`` ``+ # training_time = time.time() - start_training`` `` `` ``- self._surrogate_analyser = SurrogateAnalysisMono(training_time, training_surrogate_every, r_squared, mae, self.getGlobalMaxEvaluation(), self._n_local_search)`` ``+ # self._surrogate_analyser = SurrogateAnalysisMono(training_time, training_surrogate_every, r_squared, mae, self.getGlobalMaxEvaluation(), self._n_local_search)`` `` `` ``- # reload new surrogate function`` ``- self.load_surrogate()`` ``+ # # reload new surrogate function`` ``+ # self.load_surrogate()`` `` `` ``- # reinit ls search`` ``- self._ls_local_search = 0`` ``+ # # reinit ls search`` ``+ # self._ls_local_search = 0`` `` `` `` self.information()`` `` ``