It is proved that Minimal-to-Maximal Conversion Search is in fact not output-polynomial and the lower bound construction motivates a more detailed analysis of how certain heuristic choices in the algorithm design affect the running time.
Abstract
The Transversal Hypergraph problem is to enumerate (list) all inclusion-wise minimal hitting sets of a given hypergraph $\mathcal{H}$. It is the most important open question in enumeration whether this problem admits an output-polynomial algorithm whose running time scales polynomially with the size of $\mathcal{H}$ and the number of solutions. Currently, Minimal-to-Maximal Conversion Search (MMCS) by Murakami and Uno [DAM 2014] is the most efficient algorithm for real-world instances, but there are no worst-case performance guarantees known for it. We prove that MMCS is in fact not output-polynomial. The lower bound construction motivates a more detailed analysis of how certain heuristic choices in the algorithm design affect the running time. We conduct a thorough analysis of those heuristics and, based on this, propose new extension. We then show in extensive running time experiments that this new heuristic further improves practical performance.
Given a graph $G$ labeled with positive distances on each edge, what is the fewest number of edge distances that must be modified for $G$ to become a metric? It is known that this metric repair problem is $\mathrm{NP}$-hard on general graphs, with prior work focusing on approximations and fixed-parameter tractability with respect to properties of the input distance function. In this paper, we ask what structural properties of the graph itself make metric repair tractable. On the positive side, we give pseudo-polynomial time algorithms for series-parallel graphs, and by generalization, graphs of bounded treewidth. An immediate consequence of this result is a new algorithm for the length-bounded multicut problem, with a parameterized runtime bound in terms of the treewidth of a modestly augmented graph. Surprisingly, pseudo-polynomial time turns out to be the best one can hope for: We complement our algorithm with a proof that metric repair is weakly $\mathrm{NP}$-hard even on graphs of pathwidth at most six. We also prove that planarity does not help either, as the problem remains strongly $\mathrm{NP}$-hard even on grid graphs.
Asaf Etgar, Anna C.Gilbert, Jamie Tucker-Foltz· 0 citations
The exact domatic-number problem asks, for a fixed integer k, whether a given graph G satisfies dom(G) = k. Riege and Rothe proved DP-completeness for every fixed k>= 5, while the cases k = 3 and k = 4 remained open. We close this classification gap. The main ingredient is a polynomial-time reduction from 3SAT whose output graphs have domatic number 4 in the satisfiable case and domatic number 2 in the unsatisfiable case; in particular, the reduction never produces a graph of domatic number 3. This directly realizes the route suggested by Riege and Rothe for closing the remaining cases. Together with a simpler three-versus-two reduction, this yields DP-completeness of Exact-3-DNP and Exact-4-DNP. The proofs are constructive and give explicit graph gadgets whose local domination constraints encode truth assignments and clause satisfaction. The soundness arguments show conversely that any sufficiently large domatic partition enforces the intended consistency conditions and therefore yields a satisfying assignment. Consequently, Exact-k-DNP is DP-complete for every fixed k>= 3, completing the fixed-value classification from k = 3 onward.
We introduce $\mathsf{AmCMSO}$, an extension of counting monadic second-order logic ($\mathsf{CMSO}$) with predicates that refer to minimum- and maximum-value satisfying assignments. We establish fixed-parameter tractable model-checking meta-theorems for $\mathsf{AmCMSO}_1$ on graphs of bounded clique-width and for $\mathsf{AmCMSO}_2$ on graphs of bounded treewidth. These meta-theorems yield fixed-parameter tractable algorithms for several bilevel graph optimization problems, including interdiction and preassignment problems for solution uniquification, as well as algorithms for maximizing the diversity of optimal solutions without parameterizing by the optimum value. In contrast, allowing an optimality predicate to depend on an external set variable makes model checking hard for every level of the polynomial hierarchy, even on trees of fixed depth.
We extend the algorithmic framework of progressive exploration [Fabia\'nski et al., STACS 2019], which yields simple, yet surprisingly general and efficient parameterized algorithms for Dominating Set, Independent Set, and some of their variants. While they identified stability and the Helly property as necessary for their approach, we show that -- with a simple change -- in the case of Dominating Set, one can get rid of the stability requirement. This yields a fixed-parameter tractable algorithm on exactly those graph classes which do not contain long co-matchings or double-ladders as semi-induced subgraphs. Lifting one of these two restrictions makes Dominating Set W[1]-hard on these classes. Our algorithm generalizes results on weakly $\gamma$-closed graphs, and results from Sparsity theory, e.g., nowhere dense and biclique-free classes. At the same time, we match the time complexity of the previously known algorithms on those classes. We demonstrate that this technique can easily be applied to the Distance-$r$ Dominating Set and the Set Cover problem.
C. Cheng, Daniel Mock, Peter Rossmanith· 0 citations
Let $\mathcal F$ be a graph class that is closed under topological minors and 1-sums, has decidable membership, contains a triangle, and is not the class of all graphs. Recently, Lee, Liu, and Tsai [ICALP 2026] showed that the edge-decomposition problem into $k \geq 3$ elements of $\mathcal F$ is NP-hard. In particular, their general hardness reduction covers a long-standing problem on outerthickness (when $\mathcal F$ is the class of outerplanar graphs). On the other hand, it is well known that decomposing a graph into forests is polynomial-time solvable, as implied by work of Edmonds [J. Res. Natl. Bur. Stand. B. 1965]. In this paper, we take a first step toward determining the complexity of edge-decomposition problems into just two graphs (the case $k=2$). We consider the simplest possible graph class $\mathcal F$ satisfying the criteria above: the triangular forests, that is, graphs in which every 2-connected component is a triangle. We prove that determining whether a graph can be edge-decomposed into two triangular forests is NP-complete.
This paper provides the first truly linear-time approximation scheme for the Densest Subgraph Problem, and uses assignments arising from a flow-based formulation together with a structural carving lemma to progressively carve "sparse" parts of the graph while nearly preserving the densest subgraph.
