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- # main imports
- import logging
- # module imports
- from .Algorithm import Algorithm
- from .LocalSearch import LocalSearch
- class IteratedLocalSearch(Algorithm):
- def run(self, _evaluations, _ls_evaluations=100):
- # by default use of mother method to initialize variables
- super().run(_evaluations)
- # enable checkpoint for ILS
- if self.checkpoint is not None:
- self.resume()
- # passing global evaluation param from ILS
- ls = LocalSearch(self.initializer,
- self.evaluator,
- self.operators,
- self.policy,
- self.validator,
- self.maximise,
- _parent=self)
- # set same checkpoint if exists
- if self.checkpoint is not None:
- ls.setCheckpoint(self.checkpoint)
- # local search algorithm implementation
- while not self.stop():
- # create and search solution from local search
- newSolution = ls.run(_ls_evaluations)
- # if better solution than currently, replace it
- if self.isBetter(newSolution):
- self.bestSolution = newSolution
- # number of evaluatins increased from LocalSearch
- # increase number of evaluations and progress are then not necessary there
- #self.increaseEvaluation()
- #self.progress()
- self.information()
- logging.info("End of %s, best solution found %s" %
- (type(self).__name__, self.bestSolution))
- return self.bestSolution
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