br17.inc : 17 City TSP Data
Used by: tsp1.gms tsp2.gms tsp3.gms tsp4.gms
* 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;
