Computing a Basic Feasible Solution from a Basis

Given a linear program in standard form and a basis (a set of m linearly independent column indices), compute the associated basic solution by setting non-basic variables to zero and solving for the basic variables. Determine whether the resulting solution is a basic feasible solution by checking nonnegativity.

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Tutorial

Computing a Basic Solution

A linear program in standard form is

Ax=b,x0,A\mathbf{x} = \mathbf{b}, \qquad \mathbf{x} \geq \mathbf{0},

where AA is an m×nm \times n matrix with mnm \leq n, and bRm\mathbf{b} \in \mathbb{R}^m. A basis is a set of mm column indices B={j1,j2,,jm}\mathcal{B} = \{j_1, j_2, \ldots, j_m\} whose corresponding columns of AA form an invertible m×mm \times m matrix BB. The variables xj1,,xjmx_{j_1}, \ldots, x_{j_m} are the basic variables, collected into the vector xB\mathbf{x}_B, and the remaining nmn - m variables are non-basic.

To compute the basic solution associated with B\mathcal{B}:

  1. Set every non-basic variable to 00.
  2. Solve
BxB=bB\, \mathbf{x}_B = \mathbf{b}

for the values of the basic variables.

For example, consider

A=[101011],b=[45]A = \begin{bmatrix} 1 & 0 & 1 \\ 0 & 1 & 1 \end{bmatrix}, \qquad \mathbf{b} = \begin{bmatrix} 4 \\ 5 \end{bmatrix}

with basis B={1,2}\mathcal{B} = \{1, 2\}. The non-basic variable is x3x_3, so x3=0x_3 = 0. The basic-variable system is

[1001][x1x2]=[45],\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} \begin{bmatrix} x_1 \\ x_2 \end{bmatrix} = \begin{bmatrix} 4 \\ 5 \end{bmatrix},

which gives x1=4x_1 = 4 and x2=5x_2 = 5. The basic solution is x=(4,5,0)\mathbf{x} = (4, 5, 0).

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