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− | = [[ECE PhD Qualifying Exams|ECE Ph.D. Qualifying Exam]] in "Automatic Control" (AC)= | + | = [[ECE PhD Qualifying Exams|ECE Ph.D. Qualifying Exam]] in "Automatic Control" (AC) = |
− | =Question 3, Part 3, August 2011 = | + | |
− | :[[ECE- | + | = Question 3, Part 3, August 2011 = |
+ | |||
+ | :[[ECE-QE AC3-2011 solusion-1|Part 1]],[[ECE-QE AC3-2011 solusion-2|2]],[[ECE-QE_AC3-2011_solusion-3|3]],[[ECE-QE AC3-2011 solusion-4|4]],[[ECE-QE AC3-2011 solusion-5|5]] | ||
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+ | The '''Fundamental Theorem of Linear Programming''' that one of the basic feasible solutions is an optimal solution. So we generate all possible basic feasible solutions and select from them the optimal one. | ||
+ | |||
---- | ---- | ||
+ | |||
<math>\color{blue}\text{Solution 1:}</math> | <math>\color{blue}\text{Solution 1:}</math> | ||
− | <math>\Rightarrow x_{1}=5-2x_{2}+x_{3}=3-\frac{3}{2}x_{2}+\frac{1}{2}x_{3}</math> | + | <math>\left.\begin{matrix} |
+ | x_{1}+2x_{2}-x_{3}=5 \\ | ||
+ | 2x_{1}+3x_{2}-x_{3}=6 | ||
+ | \end{matrix}\right\}\Rightarrow x_{1}=5-2x_{2}+x_{3}=3-\frac{3}{2}x_{2}+\frac{1}{2}x_{3}</math> | ||
<math>\Rightarrow x_{2}-x_{3}=4</math> | <math>\Rightarrow x_{2}-x_{3}=4</math> | ||
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x_{3}=0 | x_{3}=0 | ||
\end{matrix}\right.</math> | \end{matrix}\right.</math> | ||
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+ | <math>\color{green} \text{This solution is not using the Fundamental Theorem of Linear Programming}</math> | ||
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− | Automatic Control (AC)- Question 3, August 2011 | + | Automatic Control (AC)- Question 3, August 2011 |
− | Go to | + | Go to |
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− | ---- | + | *Problem 1: [[ECE-QE AC3-2011 solusion-1|solutions and discussions]] |
+ | *Problem 2: [[ECE-QE AC3-2011 solusion-2|solutions and discussions]] | ||
+ | *Problem 3: [[ECE-QE_AC3-2011_solusion-3|solutions and discussions]] | ||
+ | *Problem 4: [[ECE-QE AC3-2011 solusion-4|solutions and discussions]] | ||
+ | *Problem 5: [[ECE-QE AC3-2011 solusion-5|solutions and discussions]] | ||
+ | ---- | ||
− | [[ECE PhD Qualifying Exams|Back to ECE Qualifying Exams (QE) page]] | + | <br> [[ECE PhD Qualifying Exams|Back to ECE Qualifying Exams (QE) page]] |
[[Category:ECE]] [[Category:QE]] [[Category:Automatic_Control]] [[Category:Problem_solving]] | [[Category:ECE]] [[Category:QE]] [[Category:Automatic_Control]] [[Category:Problem_solving]] |
Revision as of 19:44, 28 June 2012
ECE Ph.D. Qualifying Exam in "Automatic Control" (AC)
Question 3, Part 3, August 2011
$ \color{blue}\text{3. } \left( \text{20 pts} \right) \text{ Solve the following linear program, } $
maximize − x1 − 3x2 + 4x3
subject to x1 + 2x2 − x3 = 5
2x1 + 3x2 − x3 = 6
$ x_{1} \text{ free, } x_{2}\geq0, x_{3}\leq0. $
The Fundamental Theorem of Linear Programming that one of the basic feasible solutions is an optimal solution. So we generate all possible basic feasible solutions and select from them the optimal one.
$ \color{blue}\text{Solution 1:} $
$ \left.\begin{matrix} x_{1}+2x_{2}-x_{3}=5 \\ 2x_{1}+3x_{2}-x_{3}=6 \end{matrix}\right\}\Rightarrow x_{1}=5-2x_{2}+x_{3}=3-\frac{3}{2}x_{2}+\frac{1}{2}x_{3} $
$ \Rightarrow x_{2}-x_{3}=4 $
$ \text{It is equivalent to min } x_{1}+3x_{2}-4x_{3} =5-2x_{2}+x_{3}+3x_{2}-4x_{3} = x_{2}-3x_{3}+5, x_{2}\geq0, x_{3}\leq0 $
$ x_{2}-3x_{3}+5 = x_{2}-x_{3}-2x_{3}+5=9-2x_{3}\geq9 $
$ \text{Equivalently, } -x_{1}-3x_{2}+4x_{3}\leq-9 $
$ \text{Equality is satisfied when } x_{3}=0, x_{2} =4, x_{1}=5-2\times4=-3 $
$ \Rightarrow \left\{\begin{matrix} x_{1}=-3\\ x_{2}=4\\ x_{3}=0 \end{matrix}\right. $
$ \color{green} \text{This solution is not using the Fundamental Theorem of Linear Programming} $
$ \color{blue}\text{Solution 2:} $
One of the basic feasible solution is an optimal solution.
$ \text{The equality constraints can be represented in the form } Ax=b, A= \begin{bmatrix} a_{1}& a_{2}& a_{3} \end{bmatrix} $
$ \text{The fist basis candidate is } \begin{pmatrix} a_{1} & a_{2} \end{pmatrix} $
$ \left [ A|b \right ] =\begin{bmatrix} 1 & 2 & -1 & 5 \\ 2 & 3 & -1 & 6 \end{bmatrix} = \cdots = \begin{bmatrix} 1 & 0 & 1 & -3 \\ 0 & 1 & -1 & 4 \end{bmatrix} $
$ x^{\left( 1 \right)}= \begin{bmatrix} -3 & 4 & 0 \end{bmatrix} \text{ is BFS. } f_{1}=-9 $
$ \text{The second basis candidate is } \begin{pmatrix} a_{2} & a_{3} \end{pmatrix} $
$ \left [ A|b \right ] =\begin{bmatrix} 1 & 2 & -1 & 5 \\ 2 & 3 & -1 & 6 \end{bmatrix} = \cdots = \begin{bmatrix} 1 & 0 & 1 & -3 \\ 1 & 1 & 0 & 1 \end{bmatrix} $
$ x^{\left( 2 \right)}= \begin{bmatrix} 0 & 1 & -3 \end{bmatrix} \text{ is BFS. } f_{2}=-15 $
$ \text{The third basis candidate is } \begin{pmatrix} a_{1} & a_{3} \end{pmatrix} $
$ \left [ A|b \right ] =\begin{bmatrix} 1 & 2 & -1 & 5 \\ 2 & 3 & -1 & 6 \end{bmatrix} = \cdots = \begin{bmatrix} 0 & 1 & 1 & 4 \\ 1 & 1 & 0 & 1 \end{bmatrix} $
$ x^{\left( 2 \right)}= \begin{bmatrix} 1 & 0 & -5 \end{bmatrix} \text{ is BFS. } f_{3}=-21 $
$ \because f_{1}>f_{2}>f_{3} $
$ \therefore \text{The optimal solution is } x^{*}=\begin{bmatrix} -3 & 4 & 0 \end{bmatrix} \text{ with objective value } -9 $
Automatic Control (AC)- Question 3, August 2011
Go to
- Problem 1: solutions and discussions
- Problem 2: solutions and discussions
- Problem 3: solutions and discussions
- Problem 4: solutions and discussions
- Problem 5: solutions and discussions