## archived minilp

A fast linear programming solver library

### 4 releases

 0.2.2 May 25, 2020 May 6, 2020 May 3, 2020 Apr 11, 2020

#19 in #linear-programming

Used in 13 crates (4 directly)

Apache-2.0

150KB
3.5K SLoC

# 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.

## 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.
• Problems can be defined via an API or parsed from an MPS file.

Warning: this is an early-stage project. Although the library is already quite powerful and fast, it will probably cycle, lose precision or panic on some harder problems. Please report bugs and contribute code!

## Examples

Basic usage

``````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);
``````

For a more involved example, see examples/tsp, a solver for the travelling salesman problem.