23 releases (6 stable)
1.6.1 | Nov 26, 2023 |
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1.5.0 | Jan 18, 2023 |
1.2.2 | Aug 21, 2022 |
1.2.1 | Mar 23, 2022 |
0.4.0 | Mar 19, 2021 |
#169 in Algorithms
1,405 downloads per month
Used in 3 crates
(2 directly)
41KB
740 lines
highs
Safe rust bindings to the Highs MILP Solver. Best used from the good_lp linear programming modeler.
Usage examples
Building a problem variable by variable
use highs::{ColProblem, Sense};
fn main() {
let mut pb = ColProblem::new();
// We cannot use more then 5 units of sugar in total.
let sugar = pb.add_row(..=5);
// We cannot use more then 3 units of milk in total.
let milk = pb.add_row(..=3);
// We have a first cake that we can sell for 2€. Baking it requires 1 unit of milk and 2 of sugar.
pb.add_integer_column(2., 0.., &[(sugar, 2.), (milk, 1.)]);
// We have a second cake that we can sell for 8€. Baking it requires 2 units of milk and 3 of sugar.
pb.add_integer_column(8., 0.., &[(sugar, 3.), (milk, 2.)]);
// Find the maximal possible profit
let solution = pb.optimise(Sense::Maximise).solve().get_solution();
// The solution is to bake one cake of each sort
assert_eq!(solution.columns(), vec![1., 1.]);
}
Building a problem constraint by constraint
use highs::*;
fn main() {
let mut pb = RowProblem::new();
// Optimize 3x - 2y with x<=6 and y>=5
let x = pb.add_column(3., ..6);
let y = pb.add_column(-2., 5..);
pb.add_row(2.., &[(x, 3.), (y, 8.)]); // 2 <= x*3 + y*8
}
Dependencies
~5.5–7MB
~149K SLoC