|
|
Line 31: |
Line 31: |
| ''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> |
Line 53: |
Line 53: |
|
| |
|
| ''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== |
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