[FlopCpp] Problem using FlopC++ with GLPK

[Michal Kaut]

I think I have found the problem and solution - I tested it only on the 
first example. It turned out to be a combination of the following:
1. Osi uses upper-bound = infinity to denote unlimited variables.
2. Each solver uses a different value for infinity.
3. Since FlopC++ has to be able to initialize variables even before it 
has a solver attached, it uses 1e30 as a default (which, I believe, is 
Clp's infinity). (One could argue that you have solver attached from the 
beginning and hence it should be possible to set the correct infinity .. 
well, feel free to update the code.)
3. glpk's uses 9.9e32, so it will work with the 1e30 upper bounds as 
values. This is asking for numerical problems.
4. glpk does not recognize it has problems and happily report a wrong 
solution

So, the bottom line is that if you have unbounded variables, you should 
always change their upper bounds to the solver's infinity.
In the case of the first example, just add
x.upperLimit(N) = modello.getInfinity();
to the model. (Note that you can also use modello->getInfinity(), since 
the -> operator gives you the Osi object and it has the same function.)


One more comment on the example: in many situations, I would find it 
more practical to replace
modello.maximize( x(0) + x(1) + x(2) );
by
modello.setObjective( x(0) + x(1) + x(4) );
modello.attach();
modello.maximize();
The reason is that the attach() method creates an Osi object, so one can 
use all the Osi methods to work with it (using the overloaded '->' 
operator). You can, for example, write an MPS file:
modello->writeMps("test");
You can also replace the maximize() method and start by solving an LP 
relaxation of the problem:
modello->setObjSense(MP_model::MAXIMIZE);
modello->initialSolve();
modello->branchAndBound();


Hope this helped.

Regards,
Michal


Renato Bruni wrote:
> Hello everybody,
> 
> we have some strange behaviour using FlopC++ 1.0.6 (having inside Osi
> 0.100.0) and GLPK 4.38.
> 
> If we run the following example, with 5 variables and 2 constraints, we
> obtain solution x=(0, 2, 0, 0, 0) and objective= 2
> but the solution should be x=(4, 0, 0, 0, 0) and objective= 4
> 
> #include "flopc.hpp"
> using namespace flopc;
> #include <OsiGlpkSolverInterface.hpp>
> 
> int main() {
>     MP_model modello(new OsiGlpkSolverInterface);
>     MP_set N(5);
>     MP_variable x(N);
>     x.integer();
> 
>     MP_constraint vinc1;
>     MP_constraint vinc2;
>     vinc1 = 2*x(0) + 4*x(1) + 6*x(4) == 8;
>     vinc2 = x(0) + x(4) <= 100;
>     modello.add(vinc1);
>     modello.add(vinc2);
> 
>     modello.maximize( x(0) + x(1) + x(4) );
>     x.display("Optimal solution per x:");
> }
> 
> If we run this other example, that is the same model with 5 variables and
> 2 constraints, we obtain solution x=(4, 0, 0, 0, 96) and objective= 4
> but the solution should be, like before, x=(4, 0, 0, 0, 0) and objective= 4
> 
> #include "flopc.hpp"
> using namespace flopc;
> #include <OsiGlpkSolverInterface.hpp>
> 
> int main() {
>     MP_model modello(new OsiGlpkSolverInterface);
>     MP_set N(5);
>     MP_set S(5);
>     MP_subset<1> Sub(S);
>     Sub.insert(0);
>     Sub.insert(1);
>     Sub.insert(4);
> 
>     MP_variable x(N);
>     x.integer();
> 
>     MP_data COEFF(Sub);
> 		int i;
> 		for(i=0; i<Sub.size();i++)
> 			COEFF(i)= 2*(i+1);//vector COEFF={2,4,6}
>     COEFF.display("COEFF ");
> 
>     MP_constraint vinc1;
>     MP_constraint vinc2;
>     vinc1 = sum(Sub, COEFF(Sub)*x(Sub))==8;//2x0+4x1+6x4==8
>     vinc2 = x(0) + x(4) <= 100;
>     modello.add(vinc1);
>     modello.add(vinc2);
> 
>     modello.maximize( sum(Sub, x(Sub)) );//max(x(0)+x(1)+x(4))
>    x.display("Optimal solution per x:");
> }
> 
> Which can be the reason(s) of this incorrect behaviour?
> Are there incompatibilities between the versions of FlopC++ 1.0.6 and GLPK
> 4.38? In this case, which version of GLPK should be used?
> 
> Thanks for your help.
> Best regards,
> Renato Bruni
> 
> 
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