* TSP data and incomplete TSP model. The data is problem br17 from TSPLIB. * (http://www.iwr.uni-heidelberg.de/iwr/comopt/soft/TSPLIB95/TSPLIB.html) set ii cities / i1*i17 / i(ii) subset of cities alias (ii,jj),(i,j,k); table c(ii,jj) cost coefficients (br17 from TSPLIB) i1 i2 i3 i4 i5 i6 i7 i8 i9 i10 i11 i12 i13 i14 i15 i16 i17 i1 3 5 48 48 8 8 5 5 3 3 0 3 5 8 8 5 i2 3 3 48 48 8 8 5 5 0 0 3 0 3 8 8 5 i3 5 3 72 72 48 48 24 24 3 3 5 3 0 48 48 24 i4 48 48 74 0 6 6 12 12 48 48 48 48 74 6 6 12 i5 48 48 74 0 6 6 12 12 48 48 48 48 74 6 6 12 i6 8 8 50 6 6 0 8 8 8 8 8 8 50 0 0 8 i7 8 8 50 6 6 0 8 8 8 8 8 8 50 0 0 8 i8 5 5 26 12 12 8 8 0 5 5 5 5 26 8 8 0 i9 5 5 26 12 12 8 8 0 5 5 5 5 26 8 8 0 i10 3 0 3 48 48 8 8 5 5 0 3 0 3 8 8 5 i11 3 0 3 48 48 8 8 5 5 0 3 0 3 8 8 5 i12 0 3 5 48 48 8 8 5 5 3 3 3 5 8 8 5 i13 3 0 3 48 48 8 8 5 5 0 0 3 3 8 8 5 i14 5 3 0 72 72 48 48 24 24 3 3 5 3 48 48 24 i15 8 8 50 6 6 0 0 8 8 8 8 8 8 50 0 8 i16 8 8 50 6 6 0 0 8 8 8 8 8 8 50 0 8 i17 5 5 26 12 12 8 8 0 0 5 5 5 5 26 8 8 * * for computational work with simple minded * algorithm we can restrict size of problem * and define the model over a subset of all cities. * * variables x(ii,jj) decision variables - leg of trip z objective variable; binary variable x; equations objective total cost rowsum(ii) leave each city only once colsum(jj) arrive at each city only once; * * * the assignment problem is a relaxation of the TSP * objective.. z =e= sum((i,j), c(i,j)*x(i,j)); rowsum(i).. sum(j, x(i,j)) =e= 1; colsum(j).. sum(i, x(i,j)) =e= 1; * exclude diagonal * x.fx(ii,ii) = 0;