def __init__(self, G, w, graphFactory=lambda E: Digraph(E=E)):
TspAsBranchAndBoundProblem2.__init__(self, G, w)
if G.directed:
Ginv = graphFactory(E=[(u,v) for (v,u) in w])
winv = WeightingFunction(((u,v), w(u,v)) for (v,u) in w)
else:
Ginv = G
winv = w
self.first_vertex = sample(G.V, 1)[0]
self.D = dict(Dijkstra_shortest_distance_one_to_all(Ginv, winv, self.first_vertex))
#coding: latin1
#< full
from algoritmia.problems.tsp import TspAsBranchAndBoundProblem
from algoritmia.schemes.branchandbound import BranchAndBoundSolver
from algoritmia.datastructures.prioritydicts import MinHeapMap
from algoritmia.datastructures.graphs import UndirectedGraph, WeightingFunction
w = WeightingFunction({(0,1): 0, (0,2): 15, (0,3): 2, (1,3): 3, (1,4): 13, (2,3): 11,
(2,5): 4, (3,4): 5, (3,5): 8, (3,6): 12, (4,7): 9, (5,6): 16,
(5,8):10, (6,7): 17, (6,8): 1, (6,9): 6, (7,9): 14, (8,9): 7},
symmetrical=True)
G = UndirectedGraph(E=w.keys())
problem = TspAsBranchAndBoundProblem(G, w)
solver = BranchAndBoundSolver(problem, lambda keyvalues: MinHeapMap(keyvalues))
x, weight = solver.solve()
print('Camino', x, 'con peso', weight)
#> full