English

Minimum-weight double-tree shortcutting for Metric TSP: Bounding the approximation ratio

Data Structures and Algorithms 2008-12-30 v3

Abstract

The Metric Traveling Salesman Problem (TSP) is a classical NP-hard optimization problem. The double-tree shortcutting method for Metric TSP yields an exponentially-sized space of TSP tours, each of which approximates the optimal solution within at most a factor of 2. We consider the problem of finding among these tours the one that gives the closest approximation, i.e.\ the \emph{minimum-weight double-tree shortcutting}. Previously, we gave an efficient algorithm for this problem, and carried out its experimental analysis. In this paper, we address the related question of the worst-case approximation ratio for the minimum-weight double-tree shortcutting method. In particular, we give lower bounds on the approximation ratio in some specific metric spaces: the ratio of 2 in the discrete shortest path metric, 1.622 in the planar Euclidean metric, and 1.666 in the planar Minkowski metric. The first of these lower bounds is tight; we conjecture that the other two bounds are also tight, and in particular that the minimum-weight double-tree method provides a 1.622-approximation for planar Euclidean TSP.

Keywords

Cite

@article{arxiv.0711.2399,
  title  = {Minimum-weight double-tree shortcutting for Metric TSP: Bounding the approximation ratio},
  author = {Vladimir Deineko and Alexander Tiskin},
  journal= {arXiv preprint arXiv:0711.2399},
  year   = {2008}
}
R2 v1 2026-06-21T09:43:45.501Z