Surplus variables

Surplus Variables

A surplus variable converts a $\ge$ inequality into an equality.

It measures how much the left-hand side exceeds the required minimum.

Basic Rule

For a constraint:

\[a^Tx\ge b\]

introduce a new variable:

\[s\ge 0\]

and write:

\[a^Tx-s=b\]

The surplus variable is:

\[s=a^Tx-b\]

Because $a^Tx\ge b$, we have:

\[s\ge 0\]

Interpretation

Surplus is the amount above a minimum requirement.

For a demand constraint:

\[\text{production}\ge \text{minimum demand}\]

surplus means:

\[\text{extra production beyond minimum demand}\]

Example

Suppose:

\[3x_1+2x_2\ge 60\]

Add surplus variable $s_1\ge 0$:

\[3x_1+2x_2-s_1=60\]

Then:

\[s_1=3x_1+2x_2-60\]

If $s_1=0$, the requirement is exactly met.

If $s_1>0$, the requirement is exceeded.

Another Example

For:

\[x_1+x_2\ge 3\]

standard-form equality is:

\[x_1+x_2-s=3\]

with:

\[s\ge 0\]

Surplus vs Slack

Constraint type Variable type Equality form
$a^Tx\le b$ slack $a^Tx+s=b$
$a^Tx\ge b$ surplus $a^Tx-s=b$

Slack is unused capacity.

Surplus is excess above a requirement.

Active Constraints

If a $\ge$ constraint is active, then its surplus variable is zero.

For:

\[a^Tx-s=b\]

if:

\[a^Tx=b\]

then:

\[s=0\]

If:

\[a^Tx>b\]

then:

\[s>0\]

Matrix Form

A surplus variable adds a column with coefficient $-1$ in its constraint row.

Example:

\[3x_1+2x_2-s_1=60\]

has row:

\[\begin{bmatrix}3&2&-1\end{bmatrix}\]

if the variables are:

\[(x_1,x_2,s_1)\]

Common Mistake

For a $\ge$ constraint, subtract surplus.

Correct:

\[a^Tx-s=b, \qquad s\ge 0\]

Wrong:

\[a^Tx+s=b, \qquad s\ge 0\]

because that would imply $a^Tx\le b$.

Note About Initial Bases

Slack variables in $\le$ constraints often create identity columns.

Surplus variables create $-1$ columns, so they do not automatically give the same simple initial basis.

This matters later in simplex initialization.

Checklist

You understand surplus variables if you can:

  • convert $a^Tx\ge b$ into $a^Tx-s=b$
  • explain surplus as amount above a minimum
  • distinguish slack from surplus
  • identify active constraints by zero surplus
  • write surplus columns in matrix form

See Also

Exam checkpoint

For standard-form questions, use the course convention $\min c^Tx$ subject to $Ax=b$, $x\ge0$. Convert max objectives, add slack to $\le$, subtract surplus from $\ge$, and split free variables.

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