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# Author: Simon Blanke
# Email: [email protected]
# License: MIT License
import numpy as np
from ..local import StochasticHillClimbingOptimizer
class SimulatedAnnealingOptimizer(StochasticHillClimbingOptimizer):
def __init__(self, _main_args_, _opt_args_):
super().__init__(_main_args_, _opt_args_)
self.temp = 1
# use _consider from StochasticHillClimbingOptimizer
def _accept(self, _p_):
return np.exp(-self._score_norm(_p_) / self.temp)
def _iterate(self, i, _cand_, _p_):
_cand_ = self._stochastic_hill_climb_iter(_cand_, _p_)
self.temp = self.temp * self._opt_args_.annealing_rate
return _cand_
SimonBlanke /
Hyperactive
