Abstract
Let $\mathcal{Q}$ be a vertex subset problem on graphs. In a reconfiguration variant of $\mathcal{Q}$ we are given a graph $G$ and two feasible solutions $S_s, S_t\subseteq V(G)$ of $\mathcal{Q}$ with $|S_s|=|S_t|=k$. The problem is to determine whether there exists a sequence $S_1,\ldots,S_n$ of feasible solutions, where $S_1=S_s$, $S_n=S_t$, $|S_i|\leq k\pm 1$, and each $S_{i+1}$ results from $S_i$, $1\leq i<n$, by the addition or removal of a single vertex.We prove that for every nowhere dense class of graphs and for every integer $r\geq 1$ there exists a polynomial $p_r$ such that the reconfiguration variants of the distance-$r$ independent set problem and the distance-$r$ dominating set problem admit kernels of size $p_r(k)$. If $k$ is equal to the size of a minimum distance-$r$ dominating set, then for any fixed $\epsilon>0$ we even obtain a kernel of almost linear size $\mathcal{O}(k^{1+\epsilon})$. We then prove that if a class $\mathcal{C}$ is somewhere dense and closed under taking subgraphs, then for some value of $r\geq 1$ the reconfiguration variants of the above problems on $\mathcal{C}$ are $\mathsf{W}[1]$-hard (and in particular we cannot expect the existence of kernelization algorithms). Hence our results show that the limit of tractability for the reconfiguration variants of the distance-$r$ independent set problem and distance-$r$ dominating set problem on subgraph closed graph classes lies exactly on the boundary between nowhere denseness and somewhere denseness.
Highlights
In the reconfiguration framework we are not asked to find a feasible solution to an optimization problem Q, but rather to transform a source feasible solution Ss into a more desirable feasible target solution St such that each intermediate solution is feasible
We prove that if a class C is somewhere dense and closed under taking subgraphs, for some value of r 1 the reconfiguration variants for these problems on C are W[1]-hard
Our results show that the limit of tractability for Distance-r Independent Set Reconfiguration and Distance-r Dominating Set Reconfiguration on subgraph closed graph classes lies exactly on the boundary between nowhere denseness and somewhere denseness
Summary
In the reconfiguration framework we are not asked to find a feasible solution to an optimization problem Q, but rather to transform a source feasible solution Ss into a more desirable feasible target solution St such that each intermediate solution is feasible. The authors study mostly graph theoretical vertex subset problems, that is, solutions consist of subsets S ⊆ V (G) of the input graph G For such problems, one natural parameterization is the parameter k, a bound on the size of feasible solutions, another natural parameter is , the length of the reconfiguration sequence. Lokshtanov et al proved that Dominating Set Reconfiguration is W[1]-hard parameterized by k+ on general graphs and fixed-parameter tractable, with parameter k, for graphs excluding Kd,d as a subgraph, for any constant d (in particular on degenerate graph classes and nowhere dense classes). On the reduced instance (G , k , Ss, St) one can run a brute force algorithm to decide whether the initial instance was a positive instance
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.