Crossover Operators

One Point

cx_one_point(ind1, ind2)

Executes a one-point crossover on the two individuals, who are modified in-place.

Parameters
Returns

Two mated individuals.

Return type

Mates

cx_messy_one_point(ind1, ind2)

Executes a messy one-point crossover on the two individuals, who are modified in-place.

Parameters
Returns

Two mated individuals.

Return type

Mates


Two Point

cx_two_point(ind1, ind2)

Executes a two-point crossover on the two individuals, who are modified in-place.

Parameters
Returns

Two mated individuals.

Return type

Mates

cx_two_point_copy(ind1, ind2)

Executes a two-point crossover on the copies of the two individuals. This should be used instead of the regular cx_two_point() operator when the individuals are based on numpy arrays to avoid incorrect mating behavior due to the specifics of the numpy array datatype.

Parameters
Returns

Two mated individuals.

Return type

Mates

cx_es_two_point(ind1, ind2)

Executes a two-point crossover on the two individuals and their evolution strategies, who are modified in-place.

Parameters
Returns

Two mated individuals.

Return type

Mates

cx_es_two_point_copy(ind1, ind2)

Executes a two-point crossover on the copies of the two individuals and their evolution strategies. This should be used instead of the regular cx_es_two_point() operator when the individuals are based on numpy arrays to avoid incorrect mating behavior due to the specifics of the numpy array datatype.

Parameters
Returns

Two mated individuals.

Return type

Mates


Matched

cx_partially_matched(ind1, ind2)

Executes a partially matched crossover on the two individuals, who are modified in-place.

Parameters
Returns

Two mated individuals.

Return type

Mates

cx_uniform_partially_matched(ind1, ind2, cx_prob)

Executes a uniform partially matched crossover on the two individuals, who are modified in-place.

Parameters

  • ind1 (Individual) – The first individual.

  • ind2 (Individual) – The second individual.

  • cx_prob (float) – The probability of swapping any two traits.

Returns

Two mated individuals.

Return type

Mates


Blend

cx_blend(ind1, ind2, alpha)

Executes a blend crossover on the two individuals, who are modified in-place.

Parameters

  • ind1 (Individual) – The first individual.

  • ind2 (Individual) – The second individual.

  • alpha (float) – Extent of the interval in which the new values can be drawn for each attribute on both sides of the parents’ attributes.

Returns

Two mated individuals.

Return type

Mates

cx_es_blend(ind1, ind2, alpha)

Executes a blend crossover on the two individuals and their strategies, who are modified in-place.

Parameters

  • ind1 (Individual) – The first individual.

  • ind2 (Individual) – The second individual.

  • alpha (float) – Extent of the interval in which the new values can be drawn for each attribute on both sides of the parents’ attributes.

Returns

Two mated individuals.

Return type

Mates


Binary

cx_simulated_binary(ind1, ind2, eta)

Executes a simulated binary crossover on the two individuals, who are modified in-place.

Parameters

  • ind1 (Individual) – The first individual.

  • ind2 (Individual) – The second individual.

  • eta (float) – The crowding degree of the crossover. Higher values produce children more similar to their parents, while smaller values produce children more divergent from their parents.

Returns

Two mated individuals.

Return type

Mates

cx_simulated_binary_bounded(ind1, ind2, eta, low, up)

Executes a simulated binary bounded crossover on the two individuals, who are modified in-place.

Parameters

  • ind1 (Individual) – The first individual.

  • ind2 (Individual) – The second individual.

  • eta (float) – The crowding degree of the crossover. Higher values produce children more similar to their parents, while smaller values produce children more divergent from their parents.

  • low (NumOrSeq) – The lower bound of the search space.

  • up (NumOrSeq) – The upper bound of the search space.

Returns

Two mated individuals.

Return type

Mates


Other

cx_uniform(ind1, ind2, cx_prob)

Executes a uniform crossover on the two individuals, who are modified in-place.

Parameters

  • ind1 (Individual) – The first individual.

  • ind2 (Individual) – The second individual.

  • cx_prob (float) – The probability of swapping any two traits.

Returns

Two mated individuals.

Return type

Mates

cx_ordered(ind1, ind2)

Executes an ordered crossover on the two individuals, who are modified in-place.

Parameters
Returns

Two mated individuals.

Return type

Mates