Crate oximo_highs 

oximo-highs

HiGHS LP/MILP backend for oximo.

Wraps the highs crate (HiGHS bundled, no separate install required). Supports LP, MILP, and convex continuous QP model kinds.

Usage

Most users should depend on the umbrella oximo crate with the highs feature (enabled by default):

[dependencies]
oximo = "0.1"

To use this crate directly:

[dependencies]
oximo-highs = "0.1"
oximo-core   = "0.1"
oximo-solver = "0.1"

Quick example

use oximo_core::prelude::*;
use oximo_highs::{Highs, HighsOptions};
use oximo_solver::{Solver, SolverStatus};

let m = Model::new("toy");
let x = m.var("x").lb(0.0).build();
let y = m.var("y").lb(0.0).ub(4.0).build();
m.constraint("c1", (x + 2.0 * y).le(14.0));
m.constraint("c2", (3.0 * x - y).ge(0.0));
m.maximize(3.0 * x + 4.0 * y);

let result = Highs.solve(&m, &HighsOptions::default()).unwrap();
assert_eq!(result.status, SolverStatus::Optimal);
println!("obj = {}", result.objective.unwrap()); // 34.0
println!("x   = {}", result.value_of(x).unwrap()); // 6.0
println!("y   = {}", result.value_of(y).unwrap()); // 4.0

Quadratic programs (QP)

A quadratic objective (e.g. x.powi(2), x * y) with linear constraints is detected as QP and solved by uploading the Hessian Q via Highs_passHessian. oximo derives Q from the objective with oximo_expr::extract_quadratic; HiGHS then minimizes c'x + 0.5·x'Qx.

use oximo_core::prelude::*;
use oximo_highs::{Highs, HighsOptions};
use oximo_solver::{Solver, SolverStatus};

let m = Model::new("qp");
let x = m.var("x").lb(-10.0).ub(10.0).build();
let y = m.var("y").lb(-10.0).ub(10.0).build();
m.constraint("c", (x + y).eq(1.0));
m.minimize(x.powi(2) + y.powi(2)); // min x^2 + y^2

let result = Highs.solve(&m, &HighsOptions::default()).unwrap();
assert_eq!(result.status, SolverStatus::Optimal); // x = y = 0.5, obj = 0.5

Convexity. HiGHS supports only convex QPs. For minimization, Q must be positive semidefinite (PSD), and for maximization, Q must be negative semidefinite (NSD). HiGHS does not check this condition, so supplying an indefinite or incorrectly signed Hessian may lead to incorrect or non-optimal solutions.

HiGHS does not support MIQP (integer + quadratic, returned as UnsupportedKind) or quadratic constraints (returned as Nonlinear).

Options

HighsOptions is a typed builder. All methods return Self for chaining.

Method	Type	HiGHS option	Default
.time_limit(Duration)	universal	time_limit	none
.threads(usize)	universal	threads	none
.verbose(bool)	universal	output_flag, log_to_console	none
.mip_gap(f64)	HiGHS-only	mip_rel_gap	none
.presolve(HighsPresolve)	HiGHS-only	presolve	none
.method(HighsMethod)	HiGHS-only	solver	none
.parallel(bool)	HiGHS-only	parallel	none

HighsMethod variants: Choose (let HiGHS decide), Simplex, Ipm (interior-point), PdLp (first-order).

HighsPresolve variants: Off, On, Auto ("choose").

use std::time::Duration;
use oximo_highs::{HighsOptions, HighsMethod, HighsPresolve};
use oximo_solver::UniversalOptionsExt;

let opts = HighsOptions::default()
    .time_limit(Duration::from_secs(60))
    .threads(4)
    .mip_gap(0.01)
    .presolve(HighsPresolve::On)
    .method(HighsMethod::Ipm)
    .parallel(true);

Result

SolverResult fields populated on Optimal or Feasible:

• objective - objective value (adjusted for any constant term)
• primal - variable values, keyed by VarId; access via result.value_of(var)
• dual - constraint duals, keyed by ConstraintId
• reduced_costs - variable reduced costs, keyed by VarId
• solve_time - wall time measured around the HiGHS solve call

License

MIT OR Apache-2.0

Structs

Highs

HiGHS solver handle. Cheap to construct. The actual HiGHS instance is created per solve call so models can be re-used or shared across solves.

HighsOptions

HiGHS-specific solver options.

Enums

HighsMethod

HiGHS LP / root-relaxation algorithm.

HighsPresolve

HiGHS presolve options.

Functions

solve

Translate model into a HiGHS RowProblem, solve, and return the generic SolverResult.