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Register a new userThe Maximum Binary Tree Problem
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Young-San Lin
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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We introduce and investigate the approximability of the maximum binary tree problem (MBT) in directed and undirected graphs. The goal in MBT is to find a maximum-sized binary tree in a given graph. MBT is a natural variant of the well-studied longest path problem, since both can be viewed as finding a maximum-sized tree of bounded degree in a given graph. The connection to longest path motivates the study of MBT in directed acyclic graphs (DAGs), since the longest path problem is solvable efficiently in DAGs. In contrast, we show that MBT in DAGs is in fact hard: it has no efficient $exp(-O(log n/ log log n))$-approximation algorithm under the exponential time hypothesis, where $n$ is the number of vertices in the input graph. In undirected graphs, we show that MBT has no efficient $exp(-O(log^{0.63}{n}))$-approximation under the exponential time hypothesis. Our inapproximability results rely on self-improving reductions and structural properties of binary trees. We also show constant-factor inapproximability assuming $text{P} eq text{NP}$. In addition to inapproximability results, we present algorithmic results along two different flavors: (1) We design a randomized algorithm to verify if a given directed graph on $n$ vertices contains a binary tree of size $k$ in $2^k text{poly}(n)$ time. (2) Motivated by the longest heapable subsequence problem, introduced by Byers, Heeringa, Mitzenmacher, and Zervas (ANALCO 2011), which is equivalent to MBT in permutation DAGs, we design efficient algorithms for MBT in bipartite permutation graphs.
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Multiple interval graphs are variants of interval graphs where instead of a single interval, each vertex is assigned a set of intervals on the real line. We study the complexity of the MAXIMUM CLIQUE problem in several classes of multiple interval graphs. The MAXIMUM CLIQUE problem, or the problem of finding the size of the maximum clique, is known to be NP-complete for $t$-interval graphs when $tgeq 3$ and polynomial-time solvable when $t=1$. The problem is also known to be NP-complete in $t$-track graphs when $tgeq 4$ and polynomial-time solvable when $tleq 2$. We show that MAXIMUM CLIQUE is already NP-complete for unit 2-interval graphs and unit 3-track graphs. Further, we show that the problem is APX-complete for 2-interval graphs, 3-track graphs, unit 3-interval graphs and unit 4-track graphs. We also introduce two new classes of graphs called $t$-circular interval graphs and $t$-circular track graphs and study the complexity of the MAXIMUM CLIQUE problem in them. On the positive side, we present a polynomial time $t$-approximation algorithm for WEIGHTED MAXIMUM CLIQUE on $t$-interval graphs, improving earlier work with approximation ratio $4t$.
The anti-Ramsey number, $ar(G, H)$ is the minimum integer $k$ such that in any edge colouring of $G$ with $k$ colours there is a rainbow subgraph isomorphic to $H$, i.e., a copy of $H$ with each of its edges assigned a different colour. The notion was introduced by Erd{{o}}s and Simonovits in 1973. Since then the parameter has been studied extensively in combinatorics, also the particular case when $H$ is a star graph. Recently this case received the attention of researchers from the algorithm community because of its applications in interface modelling of wireless networks. To the algorithm community, the problem is known as maximum edge $q$-colouring problem. In this paper, we study the maximum edge $2$-colouring problem from the approximation algorithm point of view. The case $q=2$ is particularly interesting due to its application in real-life problems. Algorithmically, this problem is known to be NP-hard for $qge 2$. For the case of $q=2$, it is also known that no polynomial-time algorithm can approximate to a factor less than $3/2$ assuming the unique games conjecture. Feng et al. showed a $2$-approximation algorithm for this problem. Later Adamaszek and Popa presented a $5/3$-approximation algorithm with the additional assumption that the input graph has a perfect matching. Note that the obvious but the only known algorithm issues different colours to the edges of a maximum matching (say $M$) and different colours to the connected components of $G setminus M$. In this article, we give a new analysis of the aforementioned algorithm leading to an improved approximation bound for triangle-free graphs with perfect matching. We also show a new lower bound when the input graph is triangle-free. The contribution of the paper is a completely new, deeper and closer analysis of how the optimum achieves a higher number of colours than the matching based algorithm, mentioned above.
The canonical tree-decomposition theorem, given by Robertson and Seymour in their seminal graph minors series, turns out to be one of the most important tool in structural and algorithmic graph theory. In this paper, we provide the canonical tree decomposition theorem for digraphs. More precisely, we construct directed tree-decompositions of digraphs that distinguish all their tangles of order $k$, for any fixed integer $k$, in polynomial time. As an application of this canonical tree-decomposition theorem, we provide the following result for the directed disjoint paths problem: For every fixed $k$ there is a polynomial-time algorithm which, on input $G$, and source and terminal vertices $(s_1, t_1), dots, (s_k, t_k)$, either 1. determines that there is no set of pairwise vertex-disjoint paths connecting each source $s_i$ to its terminal $t_i$, or 2.finds a half-integral solution, i.e., outputs paths $P_1, dots, P_k$ such that $P_i$ links $s_i$ to $t_i$, so that every vertex of the graph is contained in at most two paths. Given known hardness results for the directed disjoint paths problem, our result cannot be improved for general digraphs, neither to fixed-parameter tractability nor to fully vertex-disjoint directed paths. As far as we are aware, this is the first time to obtain a tractable result for the $k$-disjoint paths problem for general digraphs. We expect more applications of our canonical tree-decomposition for directed results.
In the study of extensions of polytopes of combinatorial optimization problems, a notorious open question is that for the size of the smallest extended formulation of the Minimum Spanning Tree problem on a complete graph with $n$ nodes. The best known lower bound is $Omega(n^2)$, the best known upper bound is $O(n^3)$. In this note we show that the venerable fooling set method cannot be used to improve the lower bound: every fooling set for the Spanning Tree polytope has size $O(n^2)$.
Given a set of points $P$ and axis-aligned rectangles $mathcal{R}$ in the plane, a point $p in P$ is called emph{exposed} if it lies outside all rectangles in $mathcal{R}$. In the emph{max-exposure problem}, given an integer parameter $k$, we want to delete $k$ rectangles from $mathcal{R}$ so as to maximize the number of exposed points. We show that the problem is NP-hard and assuming plausible complexity conjectures is also hard to approximate even when rectangles in $mathcal{R}$ are translates of two fixed rectangles. However, if $mathcal{R}$ only consists of translates of a single rectangle, we present a polynomial-time approximation scheme. For range space defined by general rectangles, we present a simple $O(k)$ bicriteria approximation algorithm; that is by deleting $O(k^2)$ rectangles, we can expose at least $Omega(1/k)$ of the optimal number of points.
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