[gecode-users] Linear function problem

[Guido Tack]

You've probably swapped rows and columns of the matrix, please have a look at the documentation. The error says that the size of the coefficient array is different from the size of the variable array.

Cheers,
Guido

-- 
Guido Tack


On 28/08/2013, at 7:11, manel askri <askri.manel1 at gmail.com> wrote:

>  hi everyone !
> 
> I have problem with Linear function when i compile , the compiler tells me that :
> exeption Int::linear :size of arguments mismatch 
> i think that the problem is with the linear function : my code is this : 
> #include <gecode/driver.hh>
> #include <gecode/int.hh>
> #include <gecode/search.hh>
> #include <gecode/minimodel.hh>
> 
> using namespace Gecode;
> 
> class MMKP : public Script{
> 
> protected:
> 	static const int n=4 ;//number of testers
> 	static const int m=5;// number of nodes
> 	IntArgs R;
> 	IntArgs C;
> 	IntArgs B;
> 	IntArgs Dr;
> 	IntArgs Dc;
> 	IntArgs Db;
> 	IntArgs g;
> 
> 	IntVarArray a;
> 	IntVarArray k;
> 	IntVar l;
> public :
> 	enum {
>     find_Optimal_Solution, find_realizable_solution
>   };
> 	MMKP (const Options& opt) : a(*this,n*m, 0,1){
> 
> 		R=IntArgs(4,10,15,20,40);
> 		C=IntArgs(4,20,25,30,40);
> 		B=IntArgs(4,20,30,35,40);
> 
> 		Dr=IntArgs(4,5,10,15,25);
> 		Dc=IntArgs(4,15,20,35,37);
> 		Db=IntArgs(4,10,15,20,35);
> 
> 
> 		k=IntVarArray(*this,n*m ,0,100000); 
> 		Matrix <IntVarArray> results(k, n,m);
> 
> 		//creation variables
> 
> 		//IntVarArray a(*this,n*m,0,1); // Array of n*m boolean variables
> 		Matrix <IntVarArray> X (a,n,m);// Matrix "view" of the array a
> 
> 		// objectiv variable
> 		IntVar gain (*this, 1,1000000);
> 
> 
> 		//creation of constraints 
> 			// ... over rows
> 		for ( int j=0; j<n;j++)
> 		{
> 
> 				linear(*this , X.row(j),IRT_EQ,1);
> 			
> 		}
> 
> 		//... over columns
> 			// first, get the columns, we will use an intermidiare matrix XDual
> 
> 		IntVarArray b(*this, m*n,0,1);
> 		Matrix <IntVarArray> XDual (b, m, n);
> 		for (int i=0; i<m;i++)
> 		{
> 			for ( int j =0; j<n ; j++)
> 			{
> 				XDual(i,j)=X(j,i);
> 			}
> 		}
> 
> 		for (int j = 0; j < m; j++) {
> 
> 			linear(*this, Dr,XDual.row(j),IRT_NQ, R[j]);
> 		}
> 
> 		for (int j = 0; j < m; j++) {
> 			linear (*this, Dc, XDual.row(j), IRT_NQ,C[j]);
> 
> 		}
> 
> 		for (int j = 0; j < m; j++) {
> 			linear (*this, Db, XDual.row(j), IRT_NQ,B[j]);
> 
> 		}
> 		switch (opt.model()) {
>         case find_Optimal_Solution:
> 
> 			g=IntArgs(4,20,30,40,50);
> 		//Objective function
> 
> 		for (int i = 0; i < n; i++)
> 		{
> 			linear(*this, g,X.row(i), IRT_EQ, gain);
> 
> 		}
> 		for ( int i=0; i<n;i++){
> 			for ( int j =0; j<m;j++)
> 			{
> 				results(i,j)=X(i,j);
> 			}
> 		}
> 
> 		break;
> 
> 		case find_realizable_solution:
> 			for ( int i=0; i<n;i++){
> 			for ( int j =0; j<m;j++)
> 			{
> 				results(i,j)=X(i,j);
> 			}
> 		}
>         break;
> 
> 		    // post branching
>         branch(*this, a, INT_VAR_SIZE_MAX(), INT_VAL_MAX());
> 		}
> 	}
> 		// search support
>      MMKP(bool share, MMKP& s) : Script(share, s){
>       a.update(*this, share, s.a);
>     }
> 
>     virtual Space* copy(bool share) {
>       return new MMKP(share,*this);
>     }
> 
> 	    // print solution
>     void print(std::ostream& os) const  {
> 		for(int i = 0; i < n; i++) {
> 		 for(int j = 0; j < n; j++)
>            os << std::setw(4) << a[i * n + j];
> 		 os << std::endl;
> 	}
> }
> 	};
> 
> 	// main function
> int main(int argc, char* argv[]) {
>   Options opt("MMKP");
>   opt.model(MMKP::find_Optimal_Solution);
>   opt.model(MMKP::find_realizable_solution);
> 
>   opt.parse(argc,argv);
>   Script::run<MMKP,DFS,Options>(opt);
>   return 0;
> }
> 
> so thank you very much for helping me 
> _______________________________________________
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