Crate microlp 

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.

Features

• 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.
• Interruptible: time/node limits with clean resume, warm starts from known solutions, and MIP gap reporting for integer problems.

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.

Example

use microlp::{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);

Structs

LinearExpr

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

Problem

A specification of a linear programming problem.

Solution

A solution of a problem.

SolutionIter

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

SolveOptions

Options controlling a solve. Construct with SolveOptions::default and mutate the fields you need.

Stats

Statistics of a solve, available via crate::Solution::stats.

Tolerances

Expert-level numeric tolerances for a solve (see SolveOptions::tolerances).

Variable

A reference to a variable in a linear programming problem.

Enums

ComparisonOp

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

Error

An error encountered while solving a problem.

OptimizationDirection

An enum indicating whether to minimize or maximize objective function.

Status

The outcome class of a finished or interrupted solve.

VarDomain

The domain of a variable.