Quickstart

This walkthrough builds a small linear program end-to-end. HiGHS is an opt-in backend, so enable it in the project before running this example:

cargo add oximo --features highs

🔗The problem

[ \begin{aligned} \max \quad & 3x + 4y \ \text{s.t.} \quad & x + 2y \le 14 \ & 3x \ge y \ & x \le y + 2 \ & x \ge 0 \ & 0 \le y \le 4 \end{aligned} ]

🔗The full program

use oximo::prelude::*;
use oximo::solvers::Highs;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let m = Model::new("transport");

    variable!(m, x >= 0.0);
    variable!(m, 0.0 <= y <= 4.0);

    constraint!(m, c1, x + 2.0 * y <= 14.0);
    constraint!(m, c2, 3.0 * x >= y);
    constraint!(m, c3, x <= y + 2.0);
    objective!(m, Max, 3.0 * x + 4.0 * y);

    let result = Highs.solve(&m, &HighsOptions::default())?;
    println!("obj = {:?}", result.objective()); // Some(34.0)
    println!("x   = {:?}", result.value_of(x)); // Some(6.0)
    println!("y   = {:?}", result.value_of(y)); // Some(4.0)
    Ok(())
}

Run it with cargo run.

🔗Step by step

Model::new creates the model container. The variable! macro registers the variables and their bounds, while constraint! adds relations written with <=, >=, or ==. Finally, objective! declares the expression to maximize.

Every backend implements the same Solver trait, so switching from HiGHS to another compatible backend changes only the solver type and options. For a C-free continuous LP/QP/SOCP path, enable Clarabel instead:

cargo add oximo --features clarabel

See Modeling for indexed variables and nonlinear expressions, Solvers for backend capabilities, and Results for status, values, duals, and reduced costs.