Source code for metaheuristic_designer.strategies.bayesian_optimization.bayesian_optimization

"""
Bayesian Optimization strategy.
"""

from __future__ import annotations
from ...search_strategy import SearchStrategy
from ...initializer import Initializer
from ...parent_selection_base import ParentSelection
from ...operators.BO_operator import BOOperator




class BayesianOptimization(SearchStrategy):
    """
    Bayesian Optimization using a Gaussian Process surrogate.

    This strategy replaces the usual perturbation operator with a
    :class:`BOOperator`, which fits a GP model to the current
    population and uses an acquisition function to propose new
    candidates.

    Parameters
    ----------
    initializer : Initializer
        Population initializer (provides the starting points).
    parent_sel : ParentSelection, optional
        Parent selection method (default: identity).
    name : str, optional
        Display name (default ``"Bayesian Optimization"``).
    **kwargs
        Forwarded to :class:`BOOperator` (e.g., ``batch_size``,
        ``max_samples``, ``kernel``).
    """

    def __init__(self, initializer: Initializer, parent_sel: ParentSelection = None, name: str = "Bayesian Optimization", **kwargs):
        super().__init__(initializer, operator=BOOperator(**kwargs), parent_sel=parent_sel, name=name, **kwargs)