English

Red-Blue-Partitioned MST, TSP, and Matching

Data Structures and Algorithms 2018-07-26 v2

Abstract

Arkin et al.~\cite{ArkinBCCJKMM17} recently introduced \textit{partitioned pairs} network optimization problems: given a metric-weighted graph on nn pairs of nodes, the task is to color one node from each pair red and the other blue, and then to compute two separate \textit{network structures} or disjoint (node-covering) subgraphs of a specified sort, one on the graph induced by the red nodes and the other on the blue nodes. Three structures have been investigated by \cite{ArkinBCCJKMM17}---\textit{spanning trees}, \textit{traveling salesperson tours}, and \textit{perfect matchings}---and the three objectives to optimize for when computing such pairs of structures: \textit{min-sum}, \textit{min-max}, and \textit{bottleneck}. We provide improved approximation guarantees and/or strengthened hardness results for these nine NP-hard problem settings.

Keywords

Cite

@article{arxiv.1807.08065,
  title  = {Red-Blue-Partitioned MST, TSP, and Matching},
  author = {Matthew P. Johnson},
  journal= {arXiv preprint arXiv:1807.08065},
  year   = {2018}
}

Comments

full version (conference version in CCCG 2018)

R2 v1 2026-06-23T03:09:13.666Z