Outer-approximation (OA): Difference between revisions

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''Optimal Solution for the MINLP: ''<math display=inline>x_{1}=2, x_{2}=1,y_{1}=1, y_{2}=0</math><br>
''Optimal Solution for the MINLP: ''<math display=inline>x_{1}=2, x_{2}=1,y_{1}=1, y_{2}=0</math><br>


=== Code ===
=== GAMS Model ===
The following code is used to solve the above example in the General Algebraic Modeling System (GAMS):<br>
The above example can be expressed in the General Algebraic Modeling System (GAMS) as follows:<br>
<code>Variable z;<br>
<code>Variable z;<br>
Positive Variables x1, x2;<br>
Positive Variables x1, x2;<br>

Revision as of 09:11, 26 November 2021

Author: Yousef Aloufi (CHEME 6800 Fall 2021)

Introduction

Theory

Example

Numerical 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:

GAMS Model

The above example can be expressed in the General Algebraic Modeling System (GAMS) as follows:
Variable z;
Positive Variables x1, x2;
Binary Variables y1, y2;
Equations obj, c1, c2, c3, c4, c5, c6, c7;
obj.. z =e= y1 + y2 + sqr(x1) + sqr(x2);
c1.. sqr(x1 - 2) - x2 =l= 0;
c2.. x1 - 2*y1 =g= 0;
c3.. x1 - x2 - 3*sqr(1 - y1) =g= 0;
c4.. x1 + y1 - 1 =g= 0;
c5.. x2 - y2 =g= 0;
c6.. x1 + x2 =g= 3*y1;
c7.. y1 + y2 =g= 1;
x1.lo = 0; x1.up = 4;
x2.lo = 0; x2.up = 4;
model Example /all/;
option minlp = bonmin;
option optcr = 0;
solve Example minimizing z using minlp;
display z.l, x1.l, x2.l, y1.l, y2.l;

Conclusion

References