Struct SimplexSolver 

pub struct SimplexSolver {
    pub num_vars: usize,
    pub num_constraints: usize,
    pub obj: Vec<f64>,
    pub a_matrix: Vec<Vec<f64>>,
    pub rhs: Vec<f64>,
}

A tableau-based simplex solver for LP: minimize cᵀx subject to Ax ≤ b, x ≥ 0.

Uses the standard two-phase / big-M approach in the augmented tableau form. For simplicity this implementation handles only the bounded feasible case.

Fields

num_vars: usize

Number of decision variables.

num_constraints: usize

Number of constraints (rows in A).

obj: Vec<f64>

Objective coefficients c (length = num_vars).

a_matrix: Vec<Vec<f64>>

Constraint matrix A (num_constraints × num_vars).

rhs: Vec<f64>

Right-hand side b (length = num_constraints).

Implementations

impl SimplexSolver

pub fn new(obj: Vec<f64>, a_matrix: Vec<Vec<f64>>, rhs: Vec<f64>) -> Self

Create a new simplex solver instance.

pub fn solve(&self) -> Option<f64>

Solve the LP using the simplex method (minimization).

Uses the standard full-tableau form. The objective row stores the current reduced costs; a negative reduced cost means the variable can improve the objective.

Returns Some(optimal_value) if an optimal solution is found, or None if the problem is unbounded or infeasible.

Trait Implementations

impl Clone for SimplexSolver

fn clone(&self) -> SimplexSolver

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for SimplexSolver

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.