You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I'm trying to find a maximal solution for my problem. I found an example where they maximize P here, which translated to Rust would be:
let p = Variable::new();
let x = Variable::new();
let y = Variable::new();
let mut solver = Solver::new();
solver.add_constraints(&[
p |EQ(REQUIRED)| x * -3.0 + y * -4.0,
x + y |LE(REQUIRED)| 4.0,
x * 2.0 + y |LE(REQUIRED)| 5.0,
x |GE(REQUIRED)| 0.0,
y |GE(REQUIRED)| 0.0
]).unwrap();
println!("Values:");
println!("P: {}", solver.get_value(p)); // -15
println!("x: {}", solver.get_value(x)); // 1
println!("y: {}", solver.get_value(y)); // 3
Except, I don't know how to specify that I want to optimize for P. I should get the values P=-16, x=0, y=4. How can I get similar results using your Cassowary crate?
The text was updated successfully, but these errors were encountered:
I'm trying to find a maximal solution for my problem. I found an example where they maximize P here, which translated to Rust would be:
Except, I don't know how to specify that I want to optimize for P. I should get the values P=-16, x=0, y=4. How can I get similar results using your Cassowary crate?
The text was updated successfully, but these errors were encountered: