optimization/
optimization.rs

1use rs_genetics::plot;
2use rs_genetics::population::{Config, GA, InitializationStrategy, RandomInitialization, GetPopulation};
3use rs_genetics::population::Population;
4use plot::draw_fitness;
5
6fn main() {
7    fn fitness(weights: Population) -> f64 {
8        let inputs = vec![4.0, -2.0, 3.5, 5.0, -11.0, -4.7];
9        let target = 44.0;
10        match weights {
11            Population::F64(vec) => {
12                let distance: f64 = inputs.iter()
13                    .zip(&vec[0])
14                    .map(|(x, y)| x * y)
15                    .sum();
16                let result = 1.0 / ((target - distance).abs()+0.000000001);
17                result
18            }
19            _ => panic!("Expected Population::F64"),
20        }
21    }
22
23    let init_strategy = InitializationStrategy::F64(Box::new(RandomInitialization));
24    let mut config = Config::default();
25    config.num_individuals = 1000;
26    let mut ga = GA::new(init_strategy,fitness, config);
27
28    let hist = ga.evolve(100);
29    let inputs = vec![4.0, -2.0, 3.5, 5.0, -11.0, -4.7];
30    let distance: f64 = inputs.iter()
31        .zip(&ga.population.get_individual(0).unwrap())
32        .map(|(x, y)| x * y)
33        .sum();
34    println!("Solution = {}",distance);
35    draw_fitness(hist, "fitness_curve.png");
36}
optimization/optimization.rs

optimization/
optimization.rs
