描述

此crate公开了通用超启发式和一些辅助功能，可用于构建各种优化问题的求解器。

更多详情即将到来。

lib.rs:

此crate公开了通用超启发式和一些辅助功能，可用于构建优化问题的求解器。

示例

此示例演示了使用示例模型和启发式算法来最小化Rosenbrock函数。为了简约，提供了一个预构建的求解器和启发式操作模型。查看示例模块以了解如何使用crate的任意域的功能。

use rosomaxa::prelude::*;
use rosomaxa::example::*;

let random = Arc::new(DefaultRandom::default());
// examples of heuristic operator, they are domain specific. Essentially, heuristic operator
// is responsible to produce a new, potentially better solution from the given one.
let noise_op = VectorHeuristicOperatorMode::JustNoise(Noise::new_with_ratio(1., (-0.1, 0.1), random));
let delta_op = VectorHeuristicOperatorMode::JustDelta(-0.1..0.1);
let delta_power_op = VectorHeuristicOperatorMode::JustDelta(-0.5..0.5);

// add some configuration and run the solver
let (solutions, _) = Solver::default()
    .with_fitness_fn(create_rosenbrock_function())
    .with_init_solutions(vec![vec![2., 2.]])
    .with_search_operator(noise_op, "noise", 1.)
    .with_search_operator(delta_op, "delta", 0.2)
    .with_diversify_operator(delta_power_op)
    .with_termination(Some(5), Some(1000), None, None)
    .solve()
    .expect("cannot build and use solver");

// expecting at least one solution with fitness close to 0
assert_eq!(solutions.len(), 1);
let (_, fitness) = solutions.first().unwrap();
assert!(*fitness < 0.001);