The paper proposes efficient algorithms to compute the λ-backbone coloring of complete graphs with tree or forest backbones, improving upon previous approximation results.
Matching cut, perfect matching cut, and disconnected perfect matching problems are NP-complete in graphs without induced paths of length 14 or longer, and can be solved in polynomial time in 4-chordal graphs.
The authors provide an algorithmic generalization of Dirac's theorem, showing that for a 2-connected graph G, deciding whether G contains a cycle of length at least min{2δ(G-B), |V(G)|-|B|} + k can be done in time 2^O(k+|B|) * n^O(1), where B is a subset of vertices and k is an integer.
The authors study the problem of finding a maximum-cardinality set of r-cliques in an undirected graph of fixed maximum degree Δ, subject to the cliques being either vertex disjoint or edge disjoint. They provide a complete complexity classification for both the vertex-disjoint and edge-disjoint variants.
Under the asymptotic rank conjecture, the chromatic number of an n-vertex graph can be computed deterministically in O(1.99982^n) time.
This paper proposes efficient approximation algorithms for the Total Dominating Set (TDS) and Total Roman Dominating Set (TRDS) problems in unit disk graphs.
The minimum number of maximal independent set queries required to reconstruct the edges of a hidden graph with n vertices and maximum degree Δ is Ω(Δ^2 log(n/Δ)) for randomized non-adaptive algorithms and Ω(Δ^3 log n / log Δ) for deterministic non-adaptive algorithms.
The paper presents fast sequential and distributed algorithms for finding a proper (Δ+1)-edge-coloring of a graph with maximum degree Δ, with a focus on the case when Δ is constant.
The elimination distance of a graph to the class of bounded degree graphs can be efficiently computed on planar graphs.
This paper presents a novel algebraic approach to efficiently solving the Longest Path Problem (LPP) on specific classes of graphs, including trees, uniform block graphs, block graphs, and directed acyclic graphs (DAGs). The authors introduce algebraic conditions and operations that can identify and approximate the solution in polynomial time, without relying on weight or distance functions or being constrained to undirected graphs.