Struct SimplexTable 

pub struct SimplexTable { /* private fields */ }

Implementations

impl SimplexTable

pub fn solve(&mut self) -> SimplexOutput

Solve your LP problem

Try to solve the LP problem. It uses the “standard” Simplex algorithm, with Big M method There’s no timeout, so it could run for a very long time if you’re not careful. It returns a SimplexOutput, which has a description of the solution and the optimum value (if exists).

   let program = Simplex::minimize(&vec![-3.0, 1.0, -2.0])
   .with(vec![
       SimplexConstraint::LessThan(vec![2.0, -2.0, 3.0], 5.0),
       SimplexConstraint::LessThan(vec![1.0, 1.0, -1.0], 3.0),
       SimplexConstraint::LessThan(vec![1.0, -1.0, 1.0], 2.0),
   ]);
   let mut simplex = program.unwrap();
   assert_eq!(simplex.solve(), SimplexOutput::MultipleOptimum(-8.0));
   assert_eq!(simplex.get_var(1), Some(2.5));
   assert_eq!(simplex.get_var(2), Some(1.5));
   assert_eq!(simplex.get_var(3), Some(1.0));

pub fn get_var(&self, var: usize) -> Option<f64>

Gets the value of the N var in a solved problem

   let program = Simplex::minimize(&vec![-3.0, 1.0, -2.0])
   .with(vec![
       SimplexConstraint::LessThan(vec![2.0, -2.0, 3.0], 5.0),
       SimplexConstraint::LessThan(vec![1.0, 1.0, -1.0], 3.0),
       SimplexConstraint::LessThan(vec![1.0, -1.0, 1.0], 2.0),
   ]);
   let mut simplex = program.unwrap();
   assert_eq!(simplex.solve(), SimplexOutput::MultipleOptimum(-8.0));
   assert_eq!(simplex.get_var(1), Some(2.5));
   assert_eq!(simplex.get_var(2), Some(1.5));
   assert_eq!(simplex.get_var(3), Some(1.0));