I am solving a multi-objective MILP problem similar to the one below. The Pareto front generates 21 different optimal solutions that satisfy objectives of1 and of2. How do I return or access the values of x1 and x2 for let’s say optimal solution 11 on the pareto front? If I want to access these results or return them to matlab. E.g How do I access a particular value in the 11th iteration?

The code below is from the Pareto optimal front determination example by Alireza Soroudi on the GAMS site.

```
Variable of1, of2, x1, x2;
Equation eq1, eq2, eq3, eq4;
eq1.. 4*x1 - 0.5*sqr(x2) =e= of1;
eq2.. -sqr(x1) + 5*x2 =e= of2;
eq3.. 2*x1 + 3*x2 =l= 10;
eq4.. 2*x1 - x2 =g= 0;
x1.lo = 1; x1.up = 2;
x2.lo = 1; x2.up = 3;
Model pareto1 / all /;
Set counter / c1*c21 /;
Scalar E;
Parameter report(counter,*), ranges(*);
solve pareto1 using nlp maximizing of1;
ranges('OF1max') = of1.l;
ranges('OF2min') = of2.l;
solve pareto1 using nlp maximizing of2;
ranges('OF2max') = of2.l;
ranges('OF1min') = of1.l;
loop(counter,
E = (ranges('OF2max') - ranges('OF2min'))*(ord(counter) - 1)/(card(counter) - 1) + ranges('OF2min');
of2.lo = E;
solve pareto1 using nlp maximizing of2;
report(counter,'OF1') = of1.l;
report(counter,'OF2') = of2.l;
report(counter,'E') = E;
);
display report;
```