Struct GASampler 

pub struct GASampler { /* private fields */ }

Genetic Algorithm Sampler

This sampler uses a genetic algorithm to find solutions to QUBO/HOBO problems. It maintains a population of potential solutions and evolves them through selection, crossover, and mutation.

Implementations

impl GASampler

pub const fn new(seed: Option<u64>) -> Self

Create a new Genetic Algorithm sampler

Arguments

• seed - An optional random seed for reproducibility

pub const fn with_params( seed: Option<u64>, max_generations: usize, population_size: usize, ) -> Self

Create a new Genetic Algorithm sampler with custom parameters

Arguments

• seed - An optional random seed for reproducibility
• max_generations - Maximum number of generations to evolve
• population_size - Size of the population

pub const fn with_population_size(self, size: usize) -> Self

Set population size

pub const fn with_elite_fraction(self, _fraction: f64) -> Self

Set elite fraction (placeholder method)

pub const fn with_mutation_rate(self, _rate: f64) -> Self

Set mutation rate (placeholder method)

pub const fn with_advanced_params( seed: Option<u64>, max_generations: usize, population_size: usize, _crossover: CrossoverStrategy, _mutation: MutationStrategy, ) -> Self

Create a new enhanced Genetic Algorithm sampler

Arguments

• seed - An optional random seed for reproducibility
• max_generations - Maximum number of generations to evolve
• population_size - Size of the population
• crossover - Crossover strategy to use
• mutation - Mutation strategy to use

Trait Implementations

impl Sampler for GASampler

fn run_hobo( &self, hobo: &(Array<f64, IxDyn>, HashMap<String, usize>), shots: usize, ) -> SamplerResult<Vec<SampleResult>>

Run the sampler on a HOBO problem

fn run_qubo( &self, qubo: &(Array<f64, Ix2>, HashMap<String, usize>), shots: usize, ) -> SamplerResult<Vec<SampleResult>>

Run the sampler on a QUBO problem