Evolutionary

A fully extensible Rust framework for using paralyzed genetic algorithms to solve problems.

Currently, it supports coding in Binary, Real, Permuted Integers, Integers and any other coding you may want to implement. It also has built in implementation of the following genetic operators:

• Selection:
  • Roulette Wheel
  • Tournament
• Crossover:
  • Multiple Point Crossover (MPX) (Binary)
  • Partially Mapped Crossover (PMX) (Permuted)
  • Cycle Crossover (CX) (Permuted)
• Mutation:
  • Bit Flip (Binary)
  • Swap (Permuted)

As well you can code your own selection, crossover or mutation and use it on the EvolutionBuilder.

Example:

First you'll need to code your Fitness function:

use evolutionary_computing::prelude::*;

fn f(individual: &Bin) -> f64 {
    let mut sum = 0.;

    for i in 0..individual.0.len() {
        if individual.0[i] {
            sum += 1.;
        }
    }

    sum
}

#[derive(Clone)]
pub struct MaxFitness;

impl Fitness<Bin> for MaxFitness {
    fn calculate_fitness(&self, individual: &Bin) -> f64 {
        f(individual)
    }
}

Then you'll need to create a coding for you individual so you can get the response at the end:

#[derive(Clone)]
struct MaxCoding;

impl Coding<Bin> for MaxCoding {
    type Output = f64;

    fn decode(&self, individual: &Bin) -> Self::Output {
        f(individual)
    }
}

Then you will be able to build a evolution object using the EvolutionBuiler and setting all the required parameters:

fn main() {
    let mut evolution = EvolutionBuilder::new(30, 10, GeneCod::Bin, ())
        .with_fitness(MaxFitness)
        .with_selection(TournamentSelection::default())
        .with_crossover(BinCrossover::default())
        .with_mutation(BinMutation::default())
        .with_title("Max".to_string())
        .with_stop_condition(move |_, iterations, _| iterations >= 1000)
        .with_coding(MaxCoding)
        .build().unwrap();

    evolution.run();

    println!("Best individual: {:?}", evolution.current_best());
    println!("Best fitness: {}", evolution.current_best_fitness());
}

Find this and other examples in the examples folder.