English

On the Computational Complexity of the Strong Geodetic Recognition Problem

Computational Complexity 2022-08-04 v1

Abstract

A strong geodetic set of a graph~G=(V,E)G=(V,E) is a vertex set~SV(G)S \subseteq V(G) in which it is possible to cover all the remaining vertices of~V(G)SV(G) \setminus S by assigning a unique shortest path between each vertex pair of~SS. In the Strong Geodetic problem (SG) a graph~GG and a positive integer~kk are given as input and one has to decide whether~GG has a strong geodetic set of cardinality at most~kk. This problem is known to be NP-hard for general graphs. In this work we introduce the Strong Geodetic Recognition problem (SGR), which consists in determining whether even a given vertex set~SV(G)S \subseteq V(G) is strong geodetic. We demonstrate that this version is NP-complete. We investigate and compare the computational complexity of both decision problems restricted to some graph classes, deriving polynomial-time algorithms, NP-completeness proofs, and initial parameterized complexity results, including an answer to an open question in the literature for the complexity of SG for chordal graphs.

Keywords

Cite

@article{arxiv.2208.01796,
  title  = {On the Computational Complexity of the Strong Geodetic Recognition Problem},
  author = {Carlos V. G. C. Lima and Vinicius F. dos Santos and João H. G. Sousa and Sebastián A. Urrutia},
  journal= {arXiv preprint arXiv:2208.01796},
  year   = {2022}
}
R2 v1 2026-06-25T01:25:57.488Z