methods/crossover

Crossover methods for genetic algorithms.

These methods implement the crossover strategies described in the Instinct algorithm, enabling the creation of offspring with unique combinations of parent traits.

Read this file as an inheritance-policy shelf: each method answers a different question about how aggressively two parents should be mixed.

SINGLE_POINT preserves one contiguous prefix from one parent and the remaining suffix from the other,
TWO_POINT preserves a middle segment boundary instead of only one split,
UNIFORM treats each gene as an independent coin flip,
AVERAGE blends compatible numeric genes instead of copying segments.

A practical chooser for first experiments:

start with UNIFORM when you want broad mixing and do not need contiguous blocks of structure to stay together,
use SINGLE_POINT or TWO_POINT when adjacency matters and you want to preserve larger parent segments,
choose AVERAGE when the genome is meaningfully numeric and interpolation is more useful than hard parent switching.

Minimal workflow:

const broadMixing = crossover.UNIFORM;

const oneCut = crossover.SINGLE_POINT;

const twoCut = {
  ...crossover.TWO_POINT,
  config: [0.25, 0.75],
};

const blendedOffspring = crossover.AVERAGE;

flowchart LR
  Parents[Two parent genomes] --> Segment[Segment-preserving crossover]
  Parents --> GeneWise[Gene-wise crossover]
  Parents --> Blend[Numeric blending]
  Segment --> Single[SINGLE_POINT]
  Segment --> Double[TWO_POINT]
  GeneWise --> Uniform[UNIFORM]
  Blend --> Average[AVERAGE]