Outer-approximation (OA): Difference between revisions

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''Solution: ''<math display=inline>x_{1}=2, x_{2}=1</math>, Upper Bound = 7 <br>
''Solution: ''<math display=inline>x_{1}=2, x_{2}=1</math>, Upper Bound = 7 <br>


'''Step 1a:'''  Solve the MILP master problem with OA for <math display=inline> x^{*} =[2,1] </math> : <br>
'''Step 1b:'''  Solve the MILP master problem with OA for <math display=inline> x^{*} =[2,1] </math> : <br>
<math display=block>f\big(x\big) =\big( x_{1} \big)^{2} +\big( x_{2} \big)^{2},~~ \bigtriangledown  f\big(x\big)=[2x_{1}~~~~2x_{1}]^{T} ~~for~~x^{*} =[2~~~~1]^{T} </math>
<math display=block>f\big(x\big) =\big( x_{1} \big)^{2} +\big( x_{2} \big)^{2},~~ \bigtriangledown  f\big(x\big)=[2x_{1}~~~~2x_{1}]^{T} ~~for~~x^{*} =[2~~~~1]^{T} </math>
<math display=block>f\big(x^{*}\big)+ \bigtriangledown  f\big(x^{*}\big)^{T}\big(x-x^{*}\big)=5+[4~~~~2] \begin{bmatrix}x_{1}-2  \\x_{2}-1  \end{bmatrix}=5+4\big(x_{1}-2\big)+2\big(x_{2}-1\big)</math>
<math display=block>f\big(x^{*}\big)+ \bigtriangledown  f\big(x^{*}\big)^{T}\big(x-x^{*}\big)=5+[4~~~~2] \begin{bmatrix}x_{1}-2  \\x_{2}-1  \end{bmatrix}=5+4\big(x_{1}-2\big)+2\big(x_{2}-1\big)</math>
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''MILP Solution: ''<math display=inline>x_{1}=2, x_{2}=1,y_{1}=1, y_{2}=0</math>, Lower Bound = 6 <br>
''MILP Solution: ''<math display=inline>x_{1}=2, x_{2}=1,y_{1}=1, y_{2}=0</math>, Lower Bound = 6 <br>
Lower Bound<Upper Bound, Integer Cut:<math display=inline>y_{1}- y_{2}\leq 0</math>
Lower Bound < Upper Bound, Integer cut: <math display=inline>y_{1}- y_{2}\leq 0</math>
 
'''Step 2a:'''  Start from
<math display=inline>y=[1,0]</math> and solve the NLP below: <br>
''Minimize'' <math display=block> f= 1+ \big(x_{1}\big)^{2} +\big(x_{2}\big)^{2} </math>
''Subject to'' <math display=block>\big(x_{1}-2\big)^{2}-x_{2} \leq 0</math>
<math display=block>x_{1}-2 \geq 0</math>
<math display=block>x_{1}-x_{2} \geq 0</math>
<math display=block>x_{1} \geq 0</math>
<math display=block>x_{2} \geq 0</math>
<math display=block>x_{1}+x_{2} \geq 3</math>
<math display=block>0 \leq x_{1}\leq 4</math>
<math display=block>0 \leq x_{2}\leq 4</math>
''Solution: ''<math display=inline>x_{1}=2, x_{2}=1</math>, Upper Bound = 6 <br>
Upper Bound = 6 = Lower Bound, Optimum!<br>
''Optimal Solution for the MINLP: ''<math display=inline>x_{1}=2, x_{2}=1,y_{1}=1, y_{2}=0</math>, Upper Bound = 6 <br>


==Conclusion==
==Conclusion==


==References==
==References==

Revision as of 07:45, 26 November 2021

Author: Yousef Aloufi (CHEME 6800 Fall 2021)

Introduction

Theory

Example

Minimize

Subject to
Solution
Step 1a: Start from and solve the NLP below:
Minimize
Subject to
Solution: , Upper Bound = 7

Step 1b: Solve the MILP master problem with OA for  :


Minimize

Subject to

MILP Solution: , Lower Bound = 6
Lower Bound < Upper Bound, Integer cut:

Step 2a: Start from and solve the NLP below:
Minimize

Subject to
Solution: , Upper Bound = 6
Upper Bound = 6 = Lower Bound, Optimum!
Optimal Solution for the MINLP: , Upper Bound = 6

Conclusion

References