syne_tune.optimizer.schedulers.multiobjective.multi_objective_regularized_evolution module

class syne_tune.optimizer.schedulers.multiobjective.multi_objective_regularized_evolution.MultiObjectiveRegularizedEvolution(config_space, metric, mode, points_to_evaluate=None, population_size=100, sample_size=10, multiobjective_priority=None, **kwargs)[source]

Bases: RegularizedEvolution

Adapts regularized evolution algorithm by Real et al. to the multi-objective setting. Elements in the populations are scored via a multi-objective priority that is set to non-dominated sort by default. Parents are sampled from the population based on this score.

Additional arguments on top of parent class syne_tune.optimizer.schedulers.searchers.StochasticSearcher:

Parameters:

  • mode (Union[List[str], str]) – Mode to use for the metric given, can be “min” or “max”, defaults to “min”

  • population_size (int) – Size of the population, defaults to 100

  • sample_size (int) – Size of the candidate set to obtain a parent for the mutation, defaults to 10