In this work we consider the problem of finding the minimumweight loop cover of an undirected graph. This combinatorial optimization problem is called 2-matching and can be seen as a relaxation of the traveling salesman problem since one does not have a unique loop condition. We consider this problem both on the complete bipartite and complete graph embedded in a one dimensional (1D) interval, the weights are chosen as a convex function of the Euclidean distance between each couple of points. Randomness is introduced throwing the points in space independently and uniformly. We derive the average optimal cost in the limit of a large number of points. We prove that the possible solutions are characterized by the presence of shoelace loops containing two or three points of each type in the complete bipartite case, and three, four or five points in the complete one. This gives rise to an exponential number of possible solutions scaling as pN, where p is the plastic constant. This is at variance to what happens in the previously studied 1D models, such as the matching and the traveling salesman problem, where for every instance of the disorder there is only one possible solution.
Plastic number and possible optimal solutions for an Euclidean 2-matching in one dimension
Malatesta, Enrico M.
2018
Abstract
In this work we consider the problem of finding the minimumweight loop cover of an undirected graph. This combinatorial optimization problem is called 2-matching and can be seen as a relaxation of the traveling salesman problem since one does not have a unique loop condition. We consider this problem both on the complete bipartite and complete graph embedded in a one dimensional (1D) interval, the weights are chosen as a convex function of the Euclidean distance between each couple of points. Randomness is introduced throwing the points in space independently and uniformly. We derive the average optimal cost in the limit of a large number of points. We prove that the possible solutions are characterized by the presence of shoelace loops containing two or three points of each type in the complete bipartite case, and three, four or five points in the complete one. This gives rise to an exponential number of possible solutions scaling as pN, where p is the plastic constant. This is at variance to what happens in the previously studied 1D models, such as the matching and the traveling salesman problem, where for every instance of the disorder there is only one possible solution.
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