Motivated by adjacency in perfect matching polytopes, we study the shortest reconfiguration problem of perfect matchings via alternating cycles. Namely, we want to find a shortest sequence of perfect matchings which transforms one given perfect matching to another given perfect matching such that the symmetric difference of each pair of consecutive perfect matchings is a single cycle. The problem is equivalent to the combinatorial shortest path problem in perfect matching polytopes. We prove that the problem is NP-hard even when a given graph is planar or bipartite, but it can be solved in polynomial time when the graph is outerplanar.
The computational aspect of the combinatorial shortest path problem on convex polytopes is not well investigated. It is known that the combinatorial diameter is hard to determine @cite_35 even for fractional matching polytopes @cite_9 . In the literature, we find many papers on the adjacency of convex polytopes arising from combinatorial optimization problems @cite_15 @cite_12 @cite_26 @cite_5 . Among others, Papadimitriou @cite_24 proved that determining whether two given vertices are adjacent in a traveling salesman polytope is -complete. This implies that computing the combinatorial shortest path between two vertices of a traveling salesman polytope is -hard. However, to the best of the authors' knowledge, all known combinatorial polytopes with such adjacency hardness stem from -hard combinatorial optimization problems and the associated polytopes have exponentially many facets. We also point out the work on a randomized algorithm to compute a combinatorial short'' path @cite_29 .
@cite_35 @cite_26 @cite_9 @cite_29 @cite_24 @cite_5 @cite_15 @cite_12
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The (combinatorial) diameter of a polytope P ⊆ ⊆ R^d is the maximum value of a shortest path between a pair of vertices on the 1-skeleton of P, that is the graph where the nodes are given by the 0-dimensional faces of P, and the edges are given the 1-dimensional faces of P. The diameter of a polytope has been studied from many different perspectives, including a computational complexity point of view. In particular, [Frieze and Teng, 1994] showed that computing the diameter of a polytope is (weakly) NP-hard. In this paper, we show that the problem of computing the diameter is strongly NP-hard even for a polytope with a very simple structure: namely, the fractional matching polytope. We also show that computing a pair of vertices at maximum shortest path distance on the 1-skeleton of this polytope is an APX-hard problem. We prove these results by giving an exact characterization of the diameter of the fractional matching polytope, that is of independent interest. We consider the problem of determining whether two traveling salesman tours correspond to non-adjacent vertices of the convex polytope associated with the traveling salesman problem. This problem is shown to be NP-Complete for both the symmetric and nonsymmetric traveling salesman problem. Several implications are discussed. For some positive constant , we give a (3 2- )-approximation algorithm for the following problem: given a graph G_0=(V,E_0), find the shortest tour that visits every vertex at least once. This is a special case of the metric traveling salesman problem when the underlying metric is defined by shortest path distances in G_0. The result improves on the 3 2-approximation algorithm due to Christofides [C76] for this special case. Similar to Christofides, our algorithm finds a spanning tree whose cost is upper bounded by the optimum, then it finds the minimum cost Eulerian augmentation (or T-join) of that tree. The main difference is in the selection of the spanning tree. Except in certain cases where the solution of LP is nearly integral, we select the spanning tree randomly by sampling from a maximum entropy distribution defined by the linear programming relaxation. Despite the simplicity of the algorithm, the analysis builds on a variety of ideas such as properties of strongly Rayleigh measures from probability theory, graph theoretical results on the structure of near minimum cuts, and the integrality of the T-join polytope from polyhedral theory. Also, as a byproduct of our result, we show new properties of the near minimum cuts of any graph, which may be of independent interest. Abstract Many combinatorial optimization problems call for the optimization of a linear function over a certain polytope. Typically, these polytopes have an exponential number of facets. We explore the problem of finding small linear programming formulations when one may use any new variables and constraints. We show that expressing the matching and the Traveling Salesman Problem by a symmetric linear program requires exponential size. We relate the minimum size needed by a LP to express a polytope to a combinatorial parameter, point out some connections with communication complexity theory, and examine the vertex packing polytope for some classes of graphs.