Outer-approximation (OA): Difference between revisions

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<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>
<br>
<math display=block>g\big(x\big)=\big(x_{1}-2\big)^{2}-x_{2},~~ \bigtriangledown g\big(x\big)=[2x_{1}-4~~~~-1]^{T}~~for~~x^{*} =[2~~~~1]^{T} </math>
<math display=block>g\big(x\big)=\big(x_{1}-2\big)^{2}-x_{2},~~ \bigtriangledown g\big(x\big)=[2x_{1}-4~~~~-1]^{T}~~for~~x^{*} =[2~~~~1]^{T} </math>



Revision as of 06:23, 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 1a: Solve the MILP master problem with OA for  :


Minimize

Subject to

Conclusion

References