4 releases
new 0.2.2 | Oct 4, 2024 |
---|---|
0.2.1 | Jul 19, 2024 |
0.2.0 | Jul 19, 2024 |
0.1.0 | Jul 7, 2024 |
#841 in Algorithms
85 downloads per month
42KB
1K
SLoC
simple_qp
simple_qp
allows formulating Quadratic Programming (QP) problems in a symbolic way.
Define your QP without unreadable matrix initializations.
Available Solver Backends
At the moment, these are the available solver backends:
OSQP
CLARABEL
COIN CBC
: restricted to Linear Programming problems
Example Code
use simple_qp::constraint;
use simple_qp::problem_variables::ProblemVariables;
use simple_qp::solver::osqp_solver::OSQPSolver;
use simple_qp::solver::Solver;
fn main() {
let mut problem = ProblemVariables::default();
let x = problem.add_variable(Some(85.), None);
let y = problem.add_variable(Some(4.0), None);
let objective = (x - 42).square() + (y - 73).square() + (x - y).square();
let constraints = vec![
constraint!(50 <= 1.5 * (x / 3 + 2 * y) <= 100),
constraint!(x - y == 75 + 2 * y),
];
let solver = OSQPSolver::default();
let res = solver
.solve(problem, objective, constraints)
.expect("Solver error");
let x_solution = res.value(x);
let y_solution = res.value(y);
println!("x = {}, y = {}", x_solution, y_solution);
}
Acknowledgment
Thanks FlorianNAdam for the constraint!
macro.
Dependencies
~2.3–3MB
~65K SLoC