A Linear Programming modeler that is easy to use, performant with large problems, and well-typed.
```rust use goodlp::{variables, variable, coincbc, SolverModel, Solution};
fn main() { let mut vars = variables!(); let a = vars.add(variable().max(1)); let b = vars.add(variable().min(2).max(4)); let solution = vars.maximise(10 * (a - b / 5) - b) .using(coin_cbc) .with(a + 2. << b) .with(1 + a >> 4. - b) .solve()?; println!("a={} b={}", solution.value(a), solution.value(b)); println!("a + b = {}", solution.eval(a + b)); } ```
This library offers an abstraction over multiple solvers. By default, it uses cbc, but you can also activate other solvers using cargo features.
Used by default, performant, but requires to have a C compiler and the cbc C library installed.
minilp is a pure rust solver, which means it works out of the box without installing anything else.
You can activate it with :
toml
[dependencies.good_lp]
version = "0.0.4"
default-features = false
features = ["minilp"]
Then use minilp
instead of coin_cbc
in your code:
use good_lp::minilp
and then vars.maximise(objective).using(minilp)
.