arXiv subjects

Mingyu Xiao

Publications and source records attributed to Mingyu Xiao.

79 records · Page 5Linked to original sources

arXiv2016

On a generalization of Nemhauser and Trotter's local optimization theorem

Fellows, Guo, Moser and Niedermeier~[JCSS2011] proved a generalization of Nemhauser and Trotter's theorem, which applies to \textsc{Bounded-Degree Vertex Deletion} (for a fixed integer $d\geq 0$, to delete $k$ vertices of the input graph to make the maximum degree of it $\leq d$) and gets a linear-vertex kernel for $d=0$ and $1$, and a superlinear-vertex kernel for each $d\geq 2$. It is still left as an open problem whether \textsc{Bounded-Degree Vertex Deletion} admits a linear-vertex kernel for each $d\geq 3$. In this paper, we refine the generalized Nemhauser and Trotter's theorem and get a linear-vertex kernel for each $d\geq 0$.

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arXiv2014

Exact Algorithms for Dominating Induced Matching Based on Graph Partition

A dominating induced matching, also called an efficient edge domination, of a graph $G=(V,E)$ with $n=|V|$ vertices and $m=|E|$ edges is a subset $F \subseteq E$ of edges in the graph such that no two edges in $F$ share a common endpoint and each edge in $E\setminus F$ is incident with exactly one edge in $F$. It is NP-hard to decide whether a graph admits a dominating induced matching or not. In this paper, we design a $1.1467^nn^{O(1)}$-time exact algorithm for this problem, improving all previous results. This problem can be redefined as a partition problem that is to partition the vertex set of a graph into two parts $I$ and $F$, where $I$ induces an independent set (a 0-regular graph) and $F$ induces a perfect matching (a 1-regular graph). After giving several structural properties of the problem, we show that the problem always contains some "good vertices", branching on which by including them to either $I$ or $F$ we can effectively reduce the graph. This leads to a fast exact algorithm to this problem.

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arXiv2013

Exact Algorithms for Maximum Independent Set

We show that the maximum independent set problem (MIS) on an $n$-vertex graph can be solved in $1.1996^nn^{O(1)}$ time and polynomial space, which even is faster than Robson's $1.2109^{n}n^{O(1)}$-time exponential-space algorithm published in 1986. We also obtain improved algorithms for MIS in graphs with maximum degree 6 and 7, which run in time of $1.1893^nn^{O(1)}$ and $1.1970^nn^{O(1)}$, respectively. Our algorithms are obtained by using fast algorithms for MIS in low-degree graphs in a hierarchical way and making a careful analyses on the structure of bounded-degree graphs.

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arXiv2012

An Exact Algorithm for TSP in Degree-3 Graphs via Circuit Procedure and Amortization on Connectivity Structure

The paper presents an O^*(1.2312^n)-time and polynomial-space algorithm for the traveling salesman problem in an n-vertex graph with maximum degree 3. This improves the previous time bounds of O^*(1.251^n) by Iwama and Nakashima and O^*(1.260^n) by Eppstein. Our algorithm is a simple branch-and-search algorithm. The only branch rule is designed on a cut-circuit structure of a graph induced by unprocessed edges. To improve a time bound by a simple analysis on measure and conquer, we introduce an amortization scheme over the cut-circuit structure by defining the measure of an instance to be the sum of not only weights of vertices but also weights of connected components of the induced graph.

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arXiv2011

New parameterized algorithms for edge dominating set

An edge dominating set of a graph G=(V,E) is a subset M of edges in the graph such that each edge in E-M is incident with at least one edge in M. In an instance of the parameterized edge dominating set problem we are given a graph G=(V,E) and an integer k and we are asked to decide whether G has an edge dominating set of size at most k. In this paper we show that the parameterized edge dominating set problem can be solved in O^*(2.3147^k) time and polynomial space. We show that this problem can be reduced to a quadratic kernel with O(k^3) edges.

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arXiv2009

New Branching Rules: Improvements on Independent Set and Vertex Cover in Sparse Graphs

We present an $O^*(1.0919^n)$-time algorithm for finding a maximum independent set in an $n$-vertex graph with degree bounded by 3, which improves the previously known algorithm of running time $O^*(1.0977^n)$ by Bourgeois, Escoffier and Paschos [IWPEC 2008]. We also present an $O^*(1.1923^k)$-time algorithm to decide if a graph with degree bounded by 3 has a vertex cover of size $k$, which improves the previously known algorithm of running time $O^*(1.1939^k)$ by Chen, Kanj and Xia [ISAAC 2003]. Two new branching techniques, \emph{branching on a bottle} and \emph{branching on a 4-cycle}, are introduced, which help us to design simple and fast algorithms for the maximum independent set and minimum vertex cover problems and avoid tedious branching rules.

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arXiv2008

Tight Approximation Ratio of a General Greedy Splitting Algorithm for the Minimum k-Way Cut Problem

For an edge-weighted connected undirected graph, the minimum $k$-way cut problem is to find a subset of edges of minimum total weight whose removal separates the graph into $k$ connected components. The problem is NP-hard when $k$ is part of the input and W[1]-hard when $k$ is taken as a parameter. A simple algorithm for approximating a minimum $k$-way cut is to iteratively increase the number of components of the graph by $h-1$, where $2 \le h \le k$, until the graph has $k$ components. The approximation ratio of this algorithm is known for $h \le 3$ but is open for $h \ge 4$. In this paper, we consider a general algorithm that iteratively increases the number of components of the graph by $h_i-1$, where $h_1 \le h_2 \le ... \le h_q$ and $\sum_{i=1}^q (h_i-1) = k-1$. We prove that the approximation ratio of this general algorithm is $2 - (\sum_{i=1}^q {h_i \choose 2})/{k \choose 2}$, which is tight. Our result implies that the approximation ratio of the simple algorithm is $2-h/k + O(h^2/k^2)$ in general and $2-h/k$ if $k-1$ is a multiple of $h-1$.

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