Struct Pmx 

pub struct Pmx<R: Rng> { /* private fields */ }

PMX crossover operator

This struct implements CrossoverOperator trait and can be used with GA.

Returns a tuple of children, first child is created by taking a substring from parent_1, second child is created by using a substring from parent_2

It works by taking a substring from one parent, then in second parent we look at genes one by one that would be transplanted if we were transplanting from second parent, if the gene (gene_1) appares in transplanted string from parent one then we ignore it, else:

• I. We remember the gene place index (index_1)
• II. We look what gene (gene_2) is at this place (index_1) in first parent
• III. We look for gene (gene_3) place (index_2) in second parent
• IV. If this gene (gene_3) can be found in transplanted genes then we place gene_1 in index_2 place, else we go to step I. with gene_1 = gene_3

P1 : 8 4 7 3 6 2 5 1 9 0
P2 : 0 1 2 3 4 5 6 7 8 9
Ch : 0 7 4 3 6 2 5 1 8 9

Degenerated case when substring has length equal to genome length can occur.

Implementations

impl Pmx<ThreadRng>

pub fn new() -> Self

Creates new Pmx crossover operator with default RNG

impl<R: Rng> Pmx<R>

pub fn with_rng(rng: R) -> Self

Trait Implementations

impl<GeneT, IndividualT, R> CrossoverOperator<IndividualT> for Pmx<R>

where IndividualT: IndividualTrait, IndividualT::ChromosomeT: Index<usize, Output = GeneT> + Push<GeneT, PushedOut = Nothing>, GeneT: Copy + Eq + Hash, R: Rng,

fn apply( &mut self, parent_1: &IndividualT, parent_2: &IndividualT, ) -> (IndividualT, IndividualT)

Returns a tuple of children, first child is created by taking a substring from parent_1, second child is created by using a substring from parent_2

It works by taking a substring from one parent, then in second parent we look at genes one by one that would be transplanted if we were transplanting from second parent, if the gene (gene_1) appares in transplanted string from parent one then we ignore it, else:

• I. We remember the gene place index (index_1)
• II. We look what gene (gene_2) is at this place (index_1) in first parent
• III. We look for gene (gene_3) place (index_2) in second parent
• IV. If this gene (gene_3) can be found in transplanted genes then we place gene_1 in index_2 place, else we go to step I. with gene_1 = gene_3

P1 : 8 4 7 3 6 2 5 1 9 0
P2 : 0 1 2 3 4 5 6 7 8 9
Ch : 0 7 4 3 6 2 5 1 8 9

Degenerated case when substring has length equal to genome length can occur.

Arguments

• parent_1 - First parent to take part in crossover
• parent_2 - Second parent to take part in crossover