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So, I was working on my assignment for an online course and there's something I didn't understand very well. The teacher gave us this model:

$$ \begin{matrix} \max & z=3x_1 + 4x_2 \\ s.t. & 2x_1 + 3x_2 \le 1200 \\ & 2x_1 + x_2 \le 1000 \\ & x_1 + 4x_2 \le 800 \\ & x_1, x_2 \ge 0 \end{matrix} $$

And proceeded to give us the tableau for the final iteration of the Simplex Method, which looked like this:

$$ \left[\begin{array}{c|c|c|c|c|c|c} B & x_1 & x_2 & x_3 & x_4 & x_5 & b \\ \hline x_3 & 0 & 0 & 1 & -0.714 & -0.571 & 28.571 \\ \hline x_1 & 1 & 0 & 0 & 0.571 & -0.142 & 457.142 \\ \hline x_2 & 0 & 1 & 0 & -0.142 & 0.285 & 85.7142 \\ \hline z & 0 & 0 & 0 & 1.142 & 0.714 & 1714.285 \end{array}\right] $$

And finally asked us for the shadow price of $x_1$ and $x_2$ - this is where I got confused, as I thought shadow prices referred to the restrictions, not the variables.

Is there such thing as a shadow price for the variable? If so, what is its meaning and how could I find it?

All resources I found online seem to confirm that suspicion, so I don't know how to proceed. Any pointers in the right direction would be much appreciated.

RobPratt
  • 45,619

1 Answers1

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To start, let us map out the Simplex Tableau as such:

\begin{array} {|c|c|c|c|c|} \hline BV & z & \text{Variables} & RHS & RT \\ \hline z & 1 & C_{BV}^TB^{-1}N-C_{NBV}^T & C_{BV}^TB^{-1}b & - \\ \hline x_n & 0 & & & \\ \text{or} & 0 & B^{-1}A & & \\ s_n & \vdots & \text{or} & B^{-1}b & \frac{B^{-1}b}{B^{-1}A_j} \\ \text{or} & 0 & B^{-1}A_j & & \\ e_n & 0 & & & \\ \hline \end{array}

In order to figure out the "Shadow Price" of a Basic Variable (which is really the amount of allowable of change in the original coefficient of a Basic Variable before it changes our current basis) is calculated by the following equation:

$$C^\pi_j=C^T_{BV}B^{-1}Ax_j-Cx_j$$

Where $B^{-1}$ is the entire matrix under the cost-coefficients of the slack variables in the tableau, $A_j$ is the original column coefficients from the constraint of the original model of the chosen variable to calculate, and $C_j$ is the original (non-standardized) cost coefficient in the objective function of the chosen variable.

This will be made more understandable via an Example:

Suppose we want to measure the amount of allowed change of a a basic variable of the following model:

$$\max z = 3x_1+5x_2$$ $$\text{Subject to:}\qquad\qquad\qquad\qquad\qquad\qquad\qquad$$ $$x_1\le4$$ $$2x_2\le12$$ $$3x_1+2x_2\le18$$ $$x_1,x_2\ge0$$

and it has the following optimal final tableau:

\begin{array}{|c|c|} \hline BV & z &x_1 & x_2 & s_1 & s_2 & s_3 & RHS \\ \hline z & 1 & 0 & 0 & 0 & \frac{3}{2} & 1 & 36 \\ \hline s_1 & 0 & 0 & 0 & 1 & -\frac{1}{3} & -\frac{1}{3} & 2\\ x_2 & 0 & 0 & 1 & 0 & \frac{1}{2} & 0 & 6\\ x_1 & 0 & 1 & 0 & 0 & -\frac{1}{3} & \frac{1}{3} & 2\\ \hline \end{array}

and we wanted to measure the amount of change if we were to change the original cost of the basic variable $x_2$, then we can measure the allowable amount of change by doing the following to each non-basic variable in the basis:

$$c^\pi_{s_2} = [0, \Delta, 3]B^{-1}A_{s_2}-0$$ $$=[0, \Delta, 3] \begin{bmatrix} 1 & -\frac{1}{3} & -\frac{1}{3}\\ 0 & \frac{1}{2} & 0 \\ 0 & -\frac{1}{3} & \frac{1}{3} \end{bmatrix} \begin{bmatrix}0\\1\\0\end{bmatrix}$$ $$\Longrightarrow c^\pi_{s_2} = \frac{1}{2}\Delta - 1 \ge 0$$ $$\text{(We don’t want to change the basis)}$$ $$\Longrightarrow\Delta\ge2$$

and,

$$c^\pi_{s_3} = [0, \Delta, 3]B^{-1}A_{s_3}-0$$ $$= [0, \Delta, 3] \begin{bmatrix} 1 & -\frac{1}{3} & -\frac{1}{3}\\ 0 & \frac{1}{2} & 0 \\ 0 & -\frac{1}{3} & \frac{1}{3} \end{bmatrix} \begin{bmatrix}0\\0\\1\end{bmatrix}$$ $$\Longrightarrow c^\pi_{s_3} = 1$$ $$\text{(Changing $x_2$’s coefficient doesn’t effect $s_3$.)}$$

Thus, the allowable coefficients of $x_2$ that wouldn’t change the basis is $\Delta \ge 2$.

Back to the Problem:

What they may be asking us is the allowable amount of coefficient change of the basic variables $x_1$ and $x_2$, which would be the following for $x_1$:

$$C^\pi_j=[0, \Delta, 4]B^{-1}Ax_j-Cx_j$$ $$=[0, \Delta, 4] \begin{bmatrix} 1 & -0.714 & -0.571\\ 0 & 0.571 & -0.142 \\ 0 & -0.142 & 0.285 \end{bmatrix}Ax_j-Cx_j$$

For each non-basic variable in the tableau, and for $x_2$:

$$C^\pi_j=[0, 3, \Delta]B^{-1}Ax_j-Cx_j$$ $$=[0, 3, \Delta] \begin{bmatrix} 1 & -0.714 & -0.571\\ 0 & 0.571 & -0.142 \\ 0 & -0.142 & 0.285 \end{bmatrix}Ax_j-Cx_j$$

For each non-basic variable to determine the allowed change for the coefficients of the basic variables.

$$$$

Otherwise, if it isn’t this, then your instructor misspoke and meant the Shadow Price of the slack variables in which is the common convention of the term, which has been answered here.