35 research outputs found

    Parameterized Algorithms on Perfect Graphs for deletion to (r,)(r,\ell)-graphs

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    For fixed integers r,0r,\ell \geq 0, a graph GG is called an {\em (r,)(r,\ell)-graph} if the vertex set V(G)V(G) can be partitioned into rr independent sets and \ell cliques. The class of (r,)(r, \ell) graphs generalizes rr-colourable graphs (when =0)\ell =0) and hence not surprisingly, determining whether a given graph is an (r,)(r, \ell)-graph is \NP-hard even when r3r \geq 3 or 3\ell \geq 3 in general graphs. When rr and \ell are part of the input, then the recognition problem is NP-hard even if the input graph is a perfect graph (where the {\sc Chromatic Number} problem is solvable in polynomial time). It is also known to be fixed-parameter tractable (FPT) on perfect graphs when parameterized by rr and \ell. I.e. there is an f(r+\ell) \cdot n^{\Oh(1)} algorithm on perfect graphs on nn vertices where ff is some (exponential) function of rr and \ell. In this paper, we consider the parameterized complexity of the following problem, which we call {\sc Vertex Partization}. Given a perfect graph GG and positive integers r,,kr,\ell,k decide whether there exists a set SV(G)S\subseteq V(G) of size at most kk such that the deletion of SS from GG results in an (r,)(r,\ell)-graph. We obtain the following results: \begin{enumerate} \item {\sc Vertex Partization} on perfect graphs is FPT when parameterized by k+r+k+r+\ell. \item The problem does not admit any polynomial sized kernel when parameterized by k+r+k+r+\ell. In other words, in polynomial time, the input graph can not be compressed to an equivalent instance of size polynomial in k+r+k+r+\ell. In fact, our result holds even when k=0k=0. \item When r,r,\ell are universal constants, then {\sc Vertex Partization} on perfect graphs, parameterized by kk, has a polynomial sized kernel. \end{enumerate

    Parameter Analysis for Guarding Terrains

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    The Terrain Guarding problem is a well-known variant of the famous Art Gallery problem. Only second to Art Gallery, it is the most well-studied visibility problem in Discrete and Computational Geometry, which has also attracted attention from the viewpoint of Parameterized complexity. In this paper, we focus on the parameterized complexity of Terrain Guarding (both discrete and continuous) with respect to two natural parameters. First we show that, when parameterized by the number r of reflex vertices in the input terrain, the problem has a polynomial kernel. We also show that, when parameterized by the number c of minima in the terrain, Discrete Orthogonal Terrain Guarding has an XP algorithm

    Knapsack: Connectedness, Path, and Shortest-Path

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    We study the knapsack problem with graph theoretic constraints. That is, we assume that there exists a graph structure on the set of items of knapsack and the solution also needs to satisfy certain graph theoretic properties on top of knapsack constraints. In particular, we need to compute in the connected knapsack problem a connected subset of items which has maximum value subject to the size of knapsack constraint. We show that this problem is strongly NP-complete even for graphs of maximum degree four and NP-complete even for star graphs. On the other hand, we develop an algorithm running in time O(2twlogtwpoly(min{s2,d2}))O\left(2^{tw\log tw}\cdot\text{poly}(\min\{s^2,d^2\})\right) where tw,s,dtw,s,d are respectively treewidth of the graph, size, and target value of the knapsack. We further exhibit a (1ϵ)(1-\epsilon) factor approximation algorithm running in time O(2twlogtwpoly(n,1/ϵ))O\left(2^{tw\log tw}\cdot\text{poly}(n,1/\epsilon)\right) for every ϵ>0\epsilon>0. We show similar results for several other graph theoretic properties, namely path and shortest-path under the problem names path-knapsack and shortestpath-knapsack. Our results seems to indicate that connected-knapsack is computationally hardest followed by path-knapsack and shortestpath-knapsack.Comment: Under revie

    FPT Algorithms for Embedding into Low Complexity Graphic Metrics

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    The Metric Embedding problem takes as input two metric spaces (X,D_X) and (Y,D_Y), and a positive integer d. The objective is to determine whether there is an embedding F:X - > Y such that the distortion d_{F} <= d. Such an embedding is called a distortion d embedding. In parameterized complexity, the Metric Embedding problem is known to be W-hard and therefore, not expected to have an FPT algorithm. In this paper, we consider the Gen-Graph Metric Embedding problem, where the two metric spaces are graph metrics. We explore the extent of tractability of the problem in the parameterized complexity setting. We determine whether an unweighted graph metric (G,D_G) can be embedded, or bijectively embedded, into another unweighted graph metric (H,D_H), where the graph H has low structural complexity. For example, H is a cycle, or H has bounded treewidth or bounded connected treewidth. The parameters for the algorithms are chosen from the upper bound d on distortion, bound Delta on the maximum degree of H, treewidth alpha of H, and the connected treewidth alpha_{c} of H. Our general approach to these problems can be summarized as trying to understand the behavior of the shortest paths in G under a low distortion embedding into H, and the structural relation the mapping of these paths has to shortest paths in H

    Communication Complexity of Pairs of Graph Families with Applications

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    Given a graph G and a pair (mathcal{F}_1,mathcal{F}_2) of graph families, the function {sf GDISJ}_{G,{cal F}_1,{cal F}_2} takes as input, two induced subgraphs G_1 and G_2 of G, such that G_1 in mathcal{F}_1 and G_2 in mathcal{F}_2 and returns 1 if V(G_1)cap V(G_2)=emptyset and 0 otherwise. We study the communication complexity of this problem in the two-party model. In particular, we look at pairs of hereditary graph families. We show that the communication complexity of this function, when the two graph families are hereditary, is sublinear if and only if there are finitely many graphs in the intersection of these two families. Then, using concepts from parameterized complexity, we obtain nuanced upper bounds on the communication complexity of GDISJ_G,cal F_1,cal F_2. A concept related to communication protocols is that of a (mathcal{F}_1,mathcal{F}_2)-separating family of a graph G. A collection mathcal{F} of subsets of V(G) is called a (mathcal{F}_1,mathcal{F}_2)-separating family} for G, if for any two vertex disjoint induced subgraphs G_1in mathcal{F}_1,G_2in mathcal{F}_2, there is a set F in mathcal{F} with V(G_1) subseteq F and V(G_2) cap F = emptyset. Given a graph G on n vertices, for any pair (mathcal{F}_1,mathcal{F}_2) of hereditary graph families with sublinear communication complexity for GDISJ_G,cal F_1,cal F_2, we give an enumeration algorithm that finds a subexponential sized (mathcal{F}_1,mathcal{F}_2)-separating family. In fact, we give an enumeration algorithm that finds a 2^{o(k)}n^{Oh(1)} sized (mathcal{F}_1,mathcal{F}_2)-separating family; where k denotes the size of a minimum sized set S of vertices such that V(G)setminus S has a bipartition (V_1,V_2) with G[V_1] in {cal F}_1 and G[V_2]in {cal F}_2. We exhibit a wide range of applications for these separating families, to obtain combinatorial bounds, enumeration algorithms as well as exact and FPT algorithms for several problems

    Parameterized Algorithms on Perfect Graphs for Deletion to (r,l)-Graphs

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    For fixed integers r,l >= 0, a graph G is called an (r,l)-graph if the vertex set V(G) can be partitioned into r independent sets and l cliques. Such a graph is also said to have cochromatic number r+l. The class of (r,l) graphs generalizes r-colourable graphs (when l=0) and hence not surprisingly, determining whether a given graph is an (r,l)-graph is NP-hard even when r >= 3 or l >= 3 in general graphs. When r and ell are part of the input, then the recognition problem is NP-hard even if the input graph is a perfect graph (where the Chromatic Number problem is solvable in polynomial time). It is also known to be fixed-parameter tractable (FPT) on perfect graphs when parameterized by r and l. I.e. there is an f(r+l) n^O(1) algorithm on perfect graphs on n vertices where f is a function of r and l. Observe that such an algorithm is unlikely on general graphs as the problem is NP-hard even for constant r and l. In this paper, we consider the parameterized complexity of the following problem, which we call Vertex Partization. Given a perfect graph G and positive integers r,l,k decide whether there exists a set S subset or equal to V(G) of size at most k such that the deletion of S from G results in an (r,l)-graph. This problem generalizes well studied problems such as Vertex Cover (when r=1 and l=0), Odd Cycle Transversal (when r=2, l=0) and Split Vertex Deletion (when r=1=l). 1. Vertex Partization on perfect graphs is FPT when parameterized by k+r+l. 2. The problem, when parameterized by k+r+l, does not admit any polynomial sized kernel, under standard complexity theoretic assumptions. In other words, in polynomial time, the input graph cannot be compressed to an equivalent instance of size polynomial in k+r+l. In fact, our result holds even when k=0. 3. When r,ell are universal constants, then Vertex Partization on perfect graphs, parameterized by k, has a polynomial sized kernel

    Parameterized Complexity Classification of Deletion to List Matrix-Partition for Low-Order Matrices

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    Given a symmetric l x l matrix M=(m_{i,j}) with entries in {0,1,*}, a graph G and a function L : V(G) - > 2^{[l]} (where [l] = {1,2,...,l}), a list M-partition of G with respect to L is a partition of V(G) into l parts, say, V_1, V_2, ..., V_l such that for each i,j in {1,2,...,l}, (i) if m_{i,j}=0 then for any u in V_i and v in V_j, uv not in E(G), (ii) if m_{i,j}=1 then for any (distinct) u in V_i and v in V_j, uv in E(G), (iii) for each v in V(G), if v in V_i then i in L(v). We consider the Deletion to List M-Partition problem that takes as input a graph G, a list function L:V(G) - > 2^[l] and a positive integer k. The aim is to determine whether there is a k-sized set S subseteq V(G) such that G-S has a list M-partition. Many important problems like Vertex Cover, Odd Cycle Transversal, Split Vertex Deletion, Multiway Cut and Deletion to List Homomorphism are special cases of the Deletion to List M-Partition problem. In this paper, we provide a classification of the parameterized complexity of Deletion to List M-Partition, parameterized by k, (a) when M is of order at most 3, and (b) when M is of order 4 with all diagonal entries belonging to {0,1}
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