Crate dsmga2 

DSMGA-II: Dependency Structure Matrix Genetic Algorithm II

This crate implements DSMGA-II with a two-edge graphical linkage model for solving discrete optimization problems, particularly binary optimization problems.

Quick Start

use dsmga2::{Dsmga2, fitness::OneMax};

let fitness_fn = OneMax;
let mut ga = Dsmga2::new(100, &fitness_fn)
    .population_size(200)
    .max_generations(1000)
    .seed(42)
    .build();

let solution = ga.run();
println!("Best fitness: {}", ga.best_fitness());

Iterator-based Usage

use dsmga2::{Dsmga2, fitness::OneMax};

let fitness_fn = OneMax;
let mut ga = Dsmga2::new(100, &fitness_fn).build();

for state in ga.take(100) {
    if state.generation % 10 == 0 {
        println!("Gen {}: fitness = {:.2}", state.generation, state.best_fitness);
    }
}

With Callbacks

use dsmga2::{Dsmga2, fitness::OneMax};

let fitness_fn = OneMax;
let mut ga = Dsmga2::new(100, &fitness_fn).build();

ga.run_with(|state| {
    println!("Generation {}: {:.2}", state.generation, state.best_fitness);
});

Re-exports

pub use checkpoint::Checkpoint;

pub use chromosome::Chromosome;

pub use fitness::FitnessFunction;

Modules

checkpoint

Checkpoint functionality for saving and loading DSMGA2 state

chromosome

fitness

structures

utils

Structs

Dsmga2

DSMGA2: Dependency Structure Matrix Genetic Algorithm II

Dsmga2Builder

Builder for configuring DSMGA2

State

State information about the DSMGA2 run