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<math>\color{blue}\text{Discussion:}</math><br>
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'''Theorem:&nbsp;'''
  
First, the given problem need to be transformed into standard form by introducing slack variables&nbsp;<math>x_{3}</math>&nbsp;and&nbsp;<math>x_{4}</math>.<span class="texhtml"><sub></sub></span>
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A basic feasible solution is optimal if and only if the corresponding reduced cost coefficeints are all nonnegative.
  
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'''Simplex Method:'''
  
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1. Transform the given problem into standard form by introducing slack variables&nbsp;<span class="texhtml">''x''<sub>3</sub></span>&nbsp;and&nbsp;<span class="texhtml">''x''<sub>4</sub></span>.<span class="texhtml"><sub></sub></span>
  
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2. Form a canonical augmented matrix corresponding to an initial basic feasible solution.
  
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3. Calculate the reduced cost coefficients corresponding to the nonbasic variables.
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4. If&nbsp;<math>r_{j}>\geq0</math>&nbsp;for all&nbsp;<math>j</math>, stop. -- the current basic feasible solution is optimal.
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5. Select a&nbsp;<math>q</math>&nbsp;such that&nbsp;<math>r_{q}<0</math>
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6. If no&nbsp;<math>y_{iq}>0</math>, stop. -- the problem is unbounded; else, calculate&nbsp;<math>p=argmin_{i}\left \{ y_{i0}/y_{iq}:y_{iq}>0 \right \}</math>.&nbsp;
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7. Update the canonical augmented matrix by pivoting about the&nbsp;<math>(p, q)</math>&nbsp;th element.
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8. Go to step 3.<br>
  
 
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<math>\therefore \text{the optimal solution to the original problem is } x^{*}=  \begin{bmatrix} 4\\ 2 \end{bmatrix}</math><font face="serif" color="#ff0000" style="font-size: 17px;">'''<br>'''</font>  
 
<math>\therefore \text{the optimal solution to the original problem is } x^{*}=  \begin{bmatrix} 4\\ 2 \end{bmatrix}</math><font face="serif" color="#ff0000" style="font-size: 17px;">'''<br>'''</font>  
  
The maximum value for &nbsp;<font face="serif"><span class="texhtml">&nbsp;''x''<sub>1</sub> + ''x''<sub>2</sub> is 6</span><br></font>  
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The maximum value for &nbsp;<font face="serif"><span class="texhtml">&nbsp;''x''<sub>1</sub> + ''x''<sub>2</sub> is 6.</span><br></font>  
  
 
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Go to  
 
Go to  
  
*Part 1: [[ECE-QE AC3-2011 solusion-1|solutions and discussions]]  
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*Part 1: [[ECE-QE AC3-2011 solusion-1|solutions and discussions]]<br>
*Part 2: [[ECE-QE_AC3-2011_solusion-2|solutions and discussions]]
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*Part 3: [[ECE-QE AC3-2011 solusion-3|solutions and discussions]]  
 
*Part 3: [[ECE-QE AC3-2011 solusion-3|solutions and discussions]]  
 
*Part 4: [[ECE-QE AC3-2011 solusion-4|solutions and discussions]]  
 
*Part 4: [[ECE-QE AC3-2011 solusion-4|solutions and discussions]]  

Revision as of 19:34, 28 June 2012

ECE Ph.D. Qualifying Exam in "Automatic Control" (AC)

Question 3, Part 2, August 2011

Part 1,2,3,4,5

 $ \color{blue}\text{2. } \left( \text{20 pts} \right) \text{ Use the simplex method to solve the problem, } $

               maximize        x1 + x2

               $ \text{subject to } x_{1}-x_{2}\leq2 $
                                        $ x_{1}+x_{2}\leq6 $                                         

                                        $ x_{1},-x_{2}\geq0. $


Theorem: 

A basic feasible solution is optimal if and only if the corresponding reduced cost coefficeints are all nonnegative.

Simplex Method:

1. Transform the given problem into standard form by introducing slack variables x3 and x4.

2. Form a canonical augmented matrix corresponding to an initial basic feasible solution.

3. Calculate the reduced cost coefficients corresponding to the nonbasic variables.

4. If $ r_{j}>\geq0 $ for all $ j $, stop. -- the current basic feasible solution is optimal.

5. Select a $ q $ such that $ r_{q}<0 $

6. If no $ y_{iq}>0 $, stop. -- the problem is unbounded; else, calculate $ p=argmin_{i}\left \{ y_{i0}/y_{iq}:y_{iq}>0 \right \} $

7. Update the canonical augmented matrix by pivoting about the $ (p, q) $ th element.

8. Go to step 3.


$ \color{blue}\text{Solution 1:} $

   min   x1x2 
   subject to    x1x2 + x3 = 2 
                     x1 + x2 + x4 = 6 

                     $ x_{1},x_{2},x_{3},x_{4}\geq 0 $

$ \begin{matrix} 1 & -1 & 1 & 0 & 2\\ 1 & 1 & 0 & 1 & 6 \\ -1 & -1 & 0 & 0 & 0 \end{matrix} \Rightarrow \begin{matrix} 1 & -1 & 1 & 0 & 2\\ 0 & 2 & -1 & 1 & 4 \\ 0 & -2 & 1 & 0 & 2 \end{matrix} \Rightarrow \begin{matrix} 1 & 0 & \frac{1}{2} & \frac{1}{2} & 4\\ 0 & 1 & -\frac{1}{2} & \frac{1}{2} & 2 \\ 0 & 0 & 0 & 1 & 6 \end{matrix} $

$ \Rightarrow x_{1}=4, x_{2}=2, \text{the maximum value } x_{1}+x_{2}=6 $


$ \color{blue}\text{Solution 2:} $

Get standard form for simplex method   min   x1x2

                                                           subject to    x1x2 + x3 = 2

                                                                             x1 + x2 + x4 = 6

                                                                             $ x_{i}\geq0, i=1,2,3,4 $

$ \begin{matrix} & a_{1} & a_{2} & a_{3} & a_{4} & b\\ & 1 & -1 & 1 & 0 & 2\\ & 1 & 1 & 0 & 1 & 6 \\ c^{T} & -1 & -1 & 0 & 0 & 0 \end{matrix} $      $ \Rightarrow \begin{matrix} 1 & -1 & 1 & 0 & 2\\ 1 & 1 & 0 & 1 & 6 \\ 0 & 0 & 0 & 1 & 6 \end{matrix} \Rightarrow \begin{matrix} 1 & -1 & 1 & 0 & 2\\ 0 & 2 & -1 & 1 & 4 \\ 0 & 0 & 0 & 1 & 6 \end{matrix} \Rightarrow \begin{matrix} 1 & 0 & \frac{1}{2} & \frac{1}{2} & 4\\ 0 & 1 & -\frac{1}{2} & \frac{1}{2} & 2 \\ 0 & 0 & 0 & 1 & 6 \end{matrix} $

$ \therefore \text{the optimal solution to the original problem is } x^{*}= \begin{bmatrix} 4\\ 2 \end{bmatrix} $

The maximum value for   x1 + x2 is 6.


Automatic Control (AC)- Question 3, August 2011

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