@File : elitist.py @Time : 2026/05/21 15:27:28 @Author : Alejandro Marrero (amarrerd@ull.edu.es) @Version : 1.0 @Contact : amarrerd@ull.edu.es @License : (C)Copyright 2026, Alejandro Marrero @Desc : None

Elitist

Bases: Replacement

Source code in digneapy/operators/replacement/elitist.py 
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class Elitist(Replacement):
    def __init__(
        self,
        hall_of_fame: int = 1,
        attr: str = "fitness",
        seed: Optional[int | np.random.SeedSequence] = None,
    ):
        super().__init__(seed)
        self._hof = hall_of_fame
        self._attr = attr

    def __call__(
        self,
        population: Sequence[IndType],
        offspring: Sequence[IndType],
    ) -> Sequence[IndType]:
        """Returns a new population constructed using the Elitist approach.
        HoF number of individuals from the current + offspring populations are
        kept in the new population. The remaining individuals are selected from
        the offspring population.

        Args:
            population Sequence[IndType],: Current population in the algorithm
            offspring  Sequence[IndType],: Offspring population
            hof (int, optional): _description_. Defaults to 1.

        Raises:
            ValueError: Raises if the sizes of the population are different

        Returns:
            list[IndType]:
        """
        if len(population) != len(offspring):
            msg = f"The size of the current population ({len(population)}) != size of the offspring ({len(offspring)}) in elitist_replacement"
            raise ValueError(msg)

        combined_population = sorted(
            itertools.chain(population, offspring),
            key=attrgetter(self._attr),
            reverse=True,
        )
        top = combined_population[: self._hof]
        return list(top + offspring[1:])

__call__(population, offspring)

Returns a new population constructed using the Elitist approach. HoF number of individuals from the current + offspring populations are kept in the new population. The remaining individuals are selected from the offspring population.

Parameters:
  • population Sequence[IndType], –

    Current population in the algorithm

  • offspring Sequence[IndType], –

    Offspring population

  • hof (int) –

    description. Defaults to 1.
Raises:
  • ValueError –

    Raises if the sizes of the population are different
Returns:
  • Sequence[IndType] –

    list[IndType]:
Source code in digneapy/operators/replacement/elitist.py 
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def __call__(
    self,
    population: Sequence[IndType],
    offspring: Sequence[IndType],
) -> Sequence[IndType]:
    """Returns a new population constructed using the Elitist approach.
    HoF number of individuals from the current + offspring populations are
    kept in the new population. The remaining individuals are selected from
    the offspring population.

    Args:
        population Sequence[IndType],: Current population in the algorithm
        offspring  Sequence[IndType],: Offspring population
        hof (int, optional): _description_. Defaults to 1.

    Raises:
        ValueError: Raises if the sizes of the population are different

    Returns:
        list[IndType]:
    """
    if len(population) != len(offspring):
        msg = f"The size of the current population ({len(population)}) != size of the offspring ({len(offspring)}) in elitist_replacement"
        raise ValueError(msg)

    combined_population = sorted(
        itertools.chain(population, offspring),
        key=attrgetter(self._attr),
        reverse=True,
    )
    top = combined_population[: self._hof]
    return list(top + offspring[1:])