We show that the average cost for the traveling-salesman problem in two
dimensions, which is the archetypal problem in combinatorial optimization, in
the bipartite case, is simply related to the average cost of the assignment
problem with the same Euclidean, increasing, convex weights. In this way we
extend a result already known in one dimension where exact solutions are
avalaible. The recently determined average cost for the assignment when the
cost function is the square of the distance between the points provides
therefore an exact prediction EN=π1logN for
large number of points 2N. As a byproduct of our analysis also the loop
covering problem has the same optimal average cost. We also explain why this
result cannot be extended at higher dimensions. We numerically check the exact
predictions.Comment: 5 pages, 3 figure