[][src]Crate minilp

A fast linear programming solver library.

Linear programming is a technique for finding the minimum (or maximum) of a linear function of a set of continuous variables subject to linear equality and inequality constraints.


  • Pure Rust implementation.
  • Able to solve problems with hundreds of thousands of variables and constraints.
  • Incremental: add constraints to an existing solution without solving it from scratch.
  • Problems can be defined via an API or parsed from an MPS file.

Entry points

Begin by creating a Problem instance, declaring variables and adding constraints. Solving it will produce a Solution that can be used to get the optimal objective value, corresponding variable values and to add more constraints to the problem.

Alternatively, create an MpsFile by parsing a file in the MPS format.


use minilp::{Problem, OptimizationDirection, ComparisonOp};

// Maximize an objective function x + 2 * y of two variables x >= 0 and 0 <= y <= 3
let mut problem = Problem::new(OptimizationDirection::Maximize);
let x = problem.add_var(1.0, (0.0, f64::INFINITY));
let y = problem.add_var(2.0, (0.0, 3.0));

// subject to constraints: x + y <= 4 and 2 * x + y >= 2.
problem.add_constraint(&[(x, 1.0), (y, 1.0)], ComparisonOp::Le, 4.0);
problem.add_constraint(&[(x, 2.0), (y, 1.0)], ComparisonOp::Ge, 2.0);

// Optimal value is 7, achieved at x = 1 and y = 3.
let solution = problem.solve().unwrap();
assert_eq!(solution.objective(), 7.0);
assert_eq!(solution[x], 1.0);
assert_eq!(solution[y], 3.0);



A sum of variables multiplied by constant coefficients used as a left-hand side when defining constraints.


A linear programming problem parsed from an MPS file.


A specification of a linear programming problem.


A solution of a problem: optimal objective function value and variable values.


An iterator over the variable-value pairs of a Solution.


A reference to a variable in a linear programming problem.



An operator specifying the relation between left-hand and right-hand sides of the constraint.


An error encountered while solving a problem.


An enum indicating whether to minimize or maximize objective function.