for i in V:
for j in V:
if j > i:
c[i,j] = distance(x[i],y[i],x[j],y[j])
return V,c
if __name__ == "__main__":
import sys
# Parse argument
if len(sys.argv) < 2:
print("Usage: %s instance" % sys.argv[0])
print("Using randomized example instead")
n = 200
seed = 1
random.seed(seed)
V,c = make_data(n)
else:
from read_tsplib import read_tsplib
try:
V,c,x,y = read_tsplib(sys.argv[1])
except:
print("Cannot read TSPLIB file",sys.argv[1])
exit(1)
obj,edges = solve_tsp(V,c)
print("\nOptimal tour:",edges)
print("Optimal cost:",obj)
for (i,j) in x:
if model.getVal(x[i, j]) > EPS:
edges.append((i, j))
return model.getObjVal(), edges
if __name__ == "__main__":
import sys
if len(sys.argv) < 2:
print("Usage: %s instance" % sys.argv[0])
print("using randomly generated TSP instance")
n = 200
seed = 1
random.seed(seed)
V,c,x,y = make_data(n)
else:
from read_tsplib import read_tsplib
try:
V, c, x, y = read_tsplib(sys.argv[1])
except:
print("Cannot read TSPLIB file", sys.argv[1])
exit(1)
obj, edges = solve_tsp(V, c)
print("")
print("Optimal tour:", edges)
print("Optimal cost:", obj)
print("")
