pareto_front

Crates.iopareto_front
lib.rspareto_front
version1.0.1
sourcesrc
created_at2021-10-22 00:11:01.710113
updated_at2021-10-27 05:32:32.904653
descriptionBuilds a Pareto front incrementaly.
homepage
repositoryhttps://github.com/nestordemeure/paretoFront
max_upload_size
id469119
size75,259
Nestor Demeure (nestordemeure)

documentation

https://docs.rs/pareto_front

README

Pareto Front (crates.io)

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.

Functionalities

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.

Usage

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.

Commit count: 33

cargo fmt