Crates.io | pareto_front |
lib.rs | pareto_front |
version | 1.0.1 |
source | src |
created_at | 2021-10-22 00:11:01.710113 |
updated_at | 2021-10-27 05:32:32.904653 |
description | Builds a Pareto front incrementaly. |
homepage | |
repository | https://github.com/nestordemeure/paretoFront |
max_upload_size | |
id | 469119 |
size | 75,259 |
The pareto_front
crate is a Rust library to build a Pareto front incrementaly.
This is particularly useful in multi-objectives optimization where, instead of having a single maximum that one can easily keep track off, one might want to keep track of various trade-offs, none of which is best on all axis, found during the optimization.
This crate tries to be small yet really fast and correct.
This crate gives you access to the ParetoFront
type which can be created (empty or from an iterator), updated by adding new potential elements (using the push
or the extend
method) and converted into an iterator, a slice or a vector.
The pareto_front_concurrent
feature unlocks the ConcurrentParetoFront
type which can be used to build a Pareto front inside a parallel algorithm without needing to put a lock around a ParetoFront
.
The pareto_front_serde
feature lets you serialize and deserialize the ParetoFront
type using serde.
Elements to be inserted in the Pareto front should implement the Dominate
trait:
use pareto_front::{Dominate, ParetoFront};
/// type that will be pushed in the Pareto front
#[derive(PartialEq)]
struct ParetoElement
{
cost: usize, // to be minimized
quality: f32, // to be maximized
}
/// implement the `Dominate` trait so that the elements can be pushed into the front
impl Dominate for ParetoElement
{
/// returns `true` is `self` is better than `x` on all fields that matter to us
fn dominate(&self, x: &Self) -> bool
{
(self.cost <= x.cost) && (self.quality >= x.quality) && (self != x)
}
}
New elements can be added to a Pareto front using the push
method (one can also collect
an iterator into a Pareto front):
// data to be put in the front
let x = ParetoElement { cost: 35, quality: 0.5 };
let y = ParetoElement { cost: 350, quality: 0.05 };
let z = ParetoElement { cost: 5, quality: 0.25 };
// insertions in the Pareto front
let mut front = ParetoFront::new();
front.push(x);
front.push(y);
// note that `push` returns a boolean to tell you if the point you just inserted is part of the current Pareto front
let z_is_pareto_optimal = front.push(z);
The resulting Pareto front can be converted into an iterator, a slice or a vector.