Simplex Algorithm
Solve the following optimization problem $$ \begin{alignat*}{2} & \text{maximize: } && c^Tx \ & \text{subject to: } && \begin{aligned}[t] Ax &\leq b\ x &\geq 0 \end{aligned} \end{alignat*} $$
Concrete Problem¶
1. Step I¶
Fromulating the problem and creating the first table for simplex algorithm.
Basic | \(x\) | \(y\) | \(s_{1}\) | \(s_{2}\) | Solution | Ratio |
---|---|---|---|---|---|---|
\(z\) | \(-2\) | \(-3\) | \(0\) | \(0\) | \(0\) | |
\(s_{1}\) | \(1\) | \(3\) | \(1\) | \(0\) | \(12\) | |
\(s_{2}\) | \(3\) | \(2\) | \(0\) | \(1\) | \(12\) |
2. Step II¶
We have to choose an entering variable which will increase the value of objective. So we choose any variable with negative coefficient. Here we choose \(y\).
Basic | \(x\) | \(y\) | \(s_{1}\) | \(s_{2}\) | Solution | Ratio |
---|---|---|---|---|---|---|
\(z\) | \(-2\) | \(-3\) | \(0\) | \(0\) | \(0\) | \(0\) |
\(s_{1}\) | \(1\) | \(3\) | \(1\) | \(0\) | \(12\) | \(4\) |
\(s_{2}\) | \(3\) | \(2\) | \(0\) | \(1\) | \(12\) | \(6\) |
3. Step III¶
We have to choose a leaving variable based on ratio analysis. Here we choose the variable with least positive ratio. In this table \(s_1\) has the least positive ratio, so it will leave. Now we have to perform the pivoting step.
4. Step IV¶
After pivoting we get a new table. Where we can repreat the above steps again and again till the simplex algorithm terminate. In ideal case we get no entering varable.
Basic | \(x\) | \(y\) | \(s_{1}\) | \(s_{2}\) | Solution | Ratio |
---|---|---|---|---|---|---|
\(z\) | \(-1\) | \(0\) | \(1\) | \(0\) | \(12\) | |
\(y\) | \(\frac{1}{3}\) | \(1\) | \(\frac{1}{3}\) | \(0\) | \(4\) | |
\(s_{2}\) | \(\frac{7}{3}\) | \(0\) | \(- \frac{2}{3}\) | \(1\) | \(4\) |
Basic | \(x\) | \(y\) | \(s_{1}\) | \(s_{2}\) | Solution | Ratio |
---|---|---|---|---|---|---|
\(z\) | \(-1\) | \(0\) | \(1\) | \(0\) | \(12\) | \(-12\) |
\(y\) | \(\frac{1}{3}\) | \(1\) | \(\frac{1}{3}\) | \(0\) | \(4\) | \(12\) |
\(s_{2}\) | \(\frac{7}{3}\) | \(0\) | \(- \frac{2}{3}\) | \(1\) | \(4\) | \(\frac{12}{7}\) |
Basic | \(x\) | \(y\) | \(s_{1}\) | \(s_{2}\) | Solution | Ratio |
---|---|---|---|---|---|---|
\(z\) | \(0\) | \(0\) | \(\frac{5}{7}\) | \(\frac{3}{7}\) | \(\frac{96}{7}\) | |
\(y\) | \(0\) | \(1\) | \(\frac{3}{7}\) | \(- \frac{1}{7}\) | \(\frac{24}{7}\) | |
\(x\) | \(1\) | \(0\) | \(- \frac{2}{7}\) | \(\frac{3}{7}\) | \(\frac{12}{7}\) |
Finally we got a table with all non-negaitve coefficient corresponding to \(z\) variable. The solution of this problem is \(96/7\) at the point \((12/7, 24/7)\)
5. Problem 2¶
Solve the following optimization problem.
\(\displaystyle \left[\begin{matrix}-2 & -1 & 3 & -5 & 0 & 0 & 0 & 0\\1 & 2 & 2 & 4 & 1 & 0 & 0 & 40\\2 & -1 & 1 & 2 & 0 & 1 & 0 & 8\\4 & -2 & 1 & -1 & 0 & 0 & 1 & 10\end{matrix}\right]\)
Basic | \(x_{1}\) | \(x_{2}\) | \(x_{3}\) | \(x_{4}\) | \(s_{1}\) | \(s_{2}\) | \(s_{3}\) | Solution | Ratio |
---|---|---|---|---|---|---|---|---|---|
\(z\) | \(-2\) | \(-1\) | \(3\) | \(-5\) | \(0\) | \(0\) | \(0\) | \(0\) | |
\(s_{1}\) | \(1\) | \(2\) | \(2\) | \(4\) | \(1\) | \(0\) | \(0\) | \(40\) | |
\(s_{2}\) | \(2\) | \(-1\) | \(1\) | \(2\) | \(0\) | \(1\) | \(0\) | \(8\) | |
\(s_{3}\) | \(4\) | \(-2\) | \(1\) | \(-1\) | \(0\) | \(0\) | \(1\) | \(10\) |
Basic | \(x_{1}\) | \(x_{2}\) | \(x_{3}\) | \(x_{4}\) | \(s_{1}\) | \(s_{2}\) | \(s_{3}\) | Solution | Ratio |
---|---|---|---|---|---|---|---|---|---|
\(z\) | \(-2\) | \(-1\) | \(3\) | \(-5\) | \(0\) | \(0\) | \(0\) | \(0\) | \(0\) |
\(s_{1}\) | \(1\) | \(2\) | \(2\) | \(4\) | \(1\) | \(0\) | \(0\) | \(40\) | \(10\) |
\(s_{2}\) | \(2\) | \(-1\) | \(1\) | \(2\) | \(0\) | \(1\) | \(0\) | \(8\) | \(4\) |
\(s_{3}\) | \(4\) | \(-2\) | \(1\) | \(-1\) | \(0\) | \(0\) | \(1\) | \(10\) | \(-10\) |
Basic | \(x_{1}\) | \(x_{2}\) | \(x_{3}\) | \(x_{4}\) | \(s_{1}\) | \(s_{2}\) | \(s_{3}\) | Solution | Ratio |
---|---|---|---|---|---|---|---|---|---|
\(z\) | \(3\) | \(- \frac{7}{2}\) | \(\frac{11}{2}\) | \(0\) | \(0\) | \(\frac{5}{2}\) | \(0\) | \(20\) | |
\(s_{1}\) | \(-3\) | \(4\) | \(0\) | \(0\) | \(1\) | \(-2\) | \(0\) | \(24\) | |
\(x_{4}\) | \(1\) | \(- \frac{1}{2}\) | \(\frac{1}{2}\) | \(1\) | \(0\) | \(\frac{1}{2}\) | \(0\) | \(4\) | |
\(s_{3}\) | \(5\) | \(- \frac{5}{2}\) | \(\frac{3}{2}\) | \(0\) | \(0\) | \(\frac{1}{2}\) | \(1\) | \(14\) |
Basic | \(x_{1}\) | \(x_{2}\) | \(x_{3}\) | \(x_{4}\) | \(s_{1}\) | \(s_{2}\) | \(s_{3}\) | Solution | Ratio |
---|---|---|---|---|---|---|---|---|---|
\(z\) | \(3\) | \(- \frac{7}{2}\) | \(\frac{11}{2}\) | \(0\) | \(0\) | \(\frac{5}{2}\) | \(0\) | \(20\) | \(- \frac{40}{7}\) |
\(s_{1}\) | \(-3\) | \(4\) | \(0\) | \(0\) | \(1\) | \(-2\) | \(0\) | \(24\) | \(6\) |
\(x_{4}\) | \(1\) | \(- \frac{1}{2}\) | \(\frac{1}{2}\) | \(1\) | \(0\) | \(\frac{1}{2}\) | \(0\) | \(4\) | \(-8\) |
\(s_{3}\) | \(5\) | \(- \frac{5}{2}\) | \(\frac{3}{2}\) | \(0\) | \(0\) | \(\frac{1}{2}\) | \(1\) | \(14\) | \(- \frac{28}{5}\) |
Basic | \(x_{1}\) | \(x_{2}\) | \(x_{3}\) | \(x_{4}\) | \(s_{1}\) | \(s_{2}\) | \(s_{3}\) | Solution | Ratio |
---|---|---|---|---|---|---|---|---|---|
\(z\) | \(\frac{3}{8}\) | \(0\) | \(\frac{11}{2}\) | \(0\) | \(\frac{7}{8}\) | \(\frac{3}{4}\) | \(0\) | \(41\) | |
\(x_{2}\) | \(- \frac{3}{4}\) | \(1\) | \(0\) | \(0\) | \(\frac{1}{4}\) | \(- \frac{1}{2}\) | \(0\) | \(6\) | |
\(x_{4}\) | \(\frac{5}{8}\) | \(0\) | \(\frac{1}{2}\) | \(1\) | \(\frac{1}{8}\) | \(\frac{1}{4}\) | \(0\) | \(7\) | |
\(s_{3}\) | \(\frac{25}{8}\) | \(0\) | \(\frac{3}{2}\) | \(0\) | \(\frac{5}{8}\) | \(- \frac{3}{4}\) | \(1\) | \(29\) |
Since all the coefficient corresponding to \(z\) is non-negative, hence there will be no entering variable. The simplex algorithm will terminate. The objective is \(41\) at the point \((0,6,0,7)\).
Last modified on: 2023-01-06 22:22:45