use std::convert::Infallible; use eoa_lib::{constraints::LowerThanConstraintFunction, fitness::FitnessFunction}; use nalgebra::{OVector, SVector}; pub struct ArbitraryFitness { fun: Box) -> f64> } impl ArbitraryFitness { pub fn new(fun: Box) -> f64>) -> Self { Self { fun } } } impl FitnessFunction for ArbitraryFitness { type In = SVector; type Out = f64; type Err = Infallible; fn fit(&self, inp: &Self::In) -> Result { Ok((self.fun)(*inp)) } } fn problem_g06() -> (ArbitraryFitness<2>, [LowerThanConstraintFunction, f64>; 2], f64) { ( ArbitraryFitness::new( Box::new(|vec| (vec[0] - 10.0).powi(3) + (vec[1] - 20.0).powi(3)) ), [ LowerThanConstraintFunction::new( Box::new(|vec| -(vec[0] - 5.0).powi(2) - (vec[1] - 5.0).powi(2) + 100.0) ), LowerThanConstraintFunction::new( Box::new(|vec| (vec[0] - 6.0).powi(2) + (vec[1] - 5.0).powi(2) - 82.81) ), ], -6961.8137558015 ) } fn problem_g08(eps: f64) -> (ArbitraryFitness<2>, [LowerThanConstraintFunction, f64>; 2], f64) { ( ArbitraryFitness::new( Box::new(|vec| { let num = (2.0 * std::f64::consts::PI * vec[0]).sin().powi(3) * (2.0 * std::f64::consts::PI * vec[1]).sin(); let den = vec[0].powi(3) * (vec[0] + vec[1]); -num / den }) ), [ LowerThanConstraintFunction::new( Box::new(move |vec| { let x1 = vec[0]; let x2 = vec[1]; x1.powi(2) - x2 + 1.0 }) ), LowerThanConstraintFunction::new( Box::new(move |vec| { let x1 = vec[0]; let x2 = vec[1]; 1.0 - x1 + (x2 - 4.0).powi(2) }) ), ], -0.0958250414180359 ) } pub fn problem_g11(eps: f64) -> (ArbitraryFitness<2>, [LowerThanConstraintFunction, f64>; 2], f64) { ( ArbitraryFitness::new( Box::new(|vec| { // Minimize f(x) = x1^2 + (x2 - 1)^2 vec[0].powi(2) + (vec[1] - 1.0).powi(2) }) ), [ // Equality h(x) = x2 - x1^2 = 0 // Transformed 1: h - eps >= 0 => -(h - eps) <= 0 LowerThanConstraintFunction::new( Box::new(move |vec| { let h = vec[1] - vec[0].powi(2); h - eps }) ), // Transformed 2: eps - h >= 0 => -(eps - h) <= 0 LowerThanConstraintFunction::new( Box::new(move |vec| { let h = vec[1] - vec[0].powi(2); eps - h }) ), ], 0.7499 // Best known optimum ) } pub fn problem_g24() -> (ArbitraryFitness<2>, [LowerThanConstraintFunction, f64>; 2], f64) { ( ArbitraryFitness::new( Box::new(|vec| { // Minimize f(x) = -x1 - x2 -vec[0] - vec[1] }) ), [ // g1(x) = -2x1^4 + 8x1^3 - 8x1^2 + x2 - 2 <= 0 LowerThanConstraintFunction::new( Box::new(|vec| { -2.0 * vec[0].powi(4) + 8.0 * vec[0].powi(3) - 8.0 * vec[0].powi(2) + vec[1] - 2.0 }) ), // g2(x) = -4x1^4 + 32x1^3 - 88x1^2 + 96x1 + x2 - 36 <= 0 LowerThanConstraintFunction::new( Box::new(|vec| { -4.0 * vec[0].powi(4) + 32.0 * vec[0].powi(3) - 88.0 * vec[0].powi(2) + 96.0 * vec[0] + vec[1] - 36.0 }) ), ], -5.50801327159536 // Best known optimum ) } fn main() { println!("Hello, world!"); }