oximo

oximo is a Rust algebraic modeling library for mathematical optimization. It provides a compact modeling API for variables, indexed domains, algebraic constraints, objectives, nonlinear expressions, and multiple solver backends.

• Webdocs
• API documentation
• Examples
• Repository

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

let demand = [4.0, 6.0, 5.0];

let m = Model::new("production");
variable!(m, production[p in 0..2, t in 0..3] >= 0.0);
constraint!(m, meet[t in 0..3],
    sum!(production[p, t] for p in 0..2) >= demand[t]);
objective!(m, Min, sum!(production[p, t] for p in 0..2, t in 0..3));

let mut solver = Highs;
let result = solver.solve(&m, &HighsOptions::default())?;
println!("objective = {:?}", result.objective());
# Ok::<(), Box<dyn std::error::Error>>(())

Expressions use standard Rust operators. Variable domains and bounds are declared directly in the model:

variable!(m, x >= 0.0);       // continuous
variable!(m, y, Bin);         // binary
variable!(m, z >= 0.0, Int);  // integer

constraint!(m, capacity, 2.0 * x + y <= 10.0);
objective!(m, Max, 3.0 * x + 4.0 * y);

Quadratic, nonlinear, and second-order-cone expressions are also available:

objective!(m, Min, (1.0 - x).powi(2) + 100.0 * (y - x.powi(2)).powi(2));
constraint!(m, disk, x.powi(2) + y.powi(2) <= 1.0);
soc_constraint!(m, cone, [x, y] <= t);

Problem types

oximo supports the following algebraic problem classes. Which classes can be solved depends on the selected backend:

• Linear programming (LP)
• Quadratic programming and quadratically constrained programming (QP/QCP)
• Nonlinear programming (NLP)
• Mixed-integer linear programming (MILP)
• Mixed-integer quadratic and quadratically constrained programming (MIQP/MIQCP)
• Mixed-integer nonlinear programming (MINLP)
• Second-order cone programming (SOCP/MISOCP)

Solver features

For example, use HiGHS for a bundled LP/MILP/QP solver:

[dependencies]
oximo = { version = "0.5", features = ["highs"] }

Licensed or external backends may require an installed solver, environment variables, and a valid license. See the backend documentation and the webdocs for setup details.

Results

SolverResult provides the termination status, objective value, variable values, duals, reduced costs, and (where supported) bounds, gaps, and solution pools.

License

MIT OR Apache-2.0