Struct metaheuristics_nature::Solver

pub struct Solver<F: ObjFunc>(_);

A public API for using optimization methods.

Users can simply obtain their solution and see the result.

• The method is a type that implemented Algorithm.
• The objective function is a type that implement ObjFunc.
• A basic algorithm data is hold by Context.

This type can infer the algorithm by Setting::Algorithm.

use metaheuristics_nature::{Rga, Setting, Solver, Task};

let s = Solver::solve(
    MyFunc::new(),
    Rga::default().task(Task::MinFit(1e-20)),
    |_| true, // Run without callback
);
// Get the result from objective function
let ans = s.result();
// Get the optimized XY value of your function
let x = s.best_parameters();
let y = s.best_fitness();
// Get the history reports
let reports = s.reports();

Implementations

impl<F: ObjFunc> Solver<F>

pub fn solve<S, C>(func: F, setting: S, callback: C) -> Self where
    S: Setting,
    S::Algorithm: Algorithm<F>,
    C: FnMut(&Report) -> bool, 

Create the task and run the algorithm, which may takes a lot of time.

Argument callback is a progress feedback function, returns true to keep algorithm running, same as the behavior of the while-loop.

pub fn func(&self) -> &F

Get the reference of the objective function.

It’s useful when you need to get the preprocessed data from the initialization process, which is stored in the objective function.

pub fn reports(&self) -> Vec<Report>

Get the history for plotting.

pub fn best_parameters(&self) -> &[f64]

Get the best parameters.

pub fn best_fitness(&self) -> f64

Get the best fitness.

pub fn result(&self) -> F::Result

Get the result of the objective function.