Steiner Tree问题的研究进展

Steiner树问题是经典的NP难解问题,在计算机网络布局、电路设计以及生物网络等领域都有很多应用。随着参数计算理论的发展,已经证明了无向图和有向图中的Steiner树问题都是固定参数可解的(FPT)。介绍了无向图和有向图中Steiner树问题的近似算法和参数算法,分析了一些特殊Steiner树问题的研究现状,还讨论了顶点加权Steiner树问题的研究进展。最后,提出了该问题的进一步研究方向。     

Steiner Tree问题的研究进展

Steiner树问题是经典的NP难解问题,在计算机网络布局、电路设计以及生物网络等领域都有很多应用.随着参数计算理论的发展,已经证明了无向图和有向图中的Steiner树问题都是固定参数可解的(FPT).介绍了无向图和有向图中Steiner树问题的近似算法和参数算法,分析了一些特殊Steiner树问题的研究现状,还讨论了顶点加权Steiner树问题的研究进展.最后,提出了该问题的进一步研究方向.     

支配问题的研究进展

复杂性理论中,支配问题是一类重要的问题,被广泛应用于资源分配、电话交换网络和无线传感器网络等领域。支配问题主要包括点支配集(VDS)问题和边支配集(EDS)问题两大类。人们利用动态规划、加权分治等技术对VDS和EDS问题的精确算法进行设计与分析,并通过将EDS问题转化为边覆盖集问题提出了EDS问题的近似算法。近年来对参数化支配问题做了大量研究。目前已经证明了平面图中VDS问题和一般图中EDS问题都是固定参数可解的(FPT)。利用树分解和分支搜索等技术,人们分别对平面图VDS问题和一般图EDS问题提出了一系列FPT算法。文中对VDS和EDS问题进行了分类,给出了每类问题的具体定义及其相关算法介绍,此外还对矩阵支配集问题进行了简单介绍,并提出了支配问题研究中值得关注的几个方面。     

带权无向图中反馈顶点集的固定参数枚举算法

反馈顶点集(FVS)问题是一个经典的NP-完全问题,在很多领域有重要的应用.人们对该问题进行了大量的研究,但目前还没有有效的算法枚举带权无向图的反馈顶点集.文中通过对带权无向图中反馈顶点集问题的结构的深入分析,给出了一个有效的基于分支搜索技术的固定参数枚举算法.算法将反馈顶点集问题转化为反馈边集问题,通过枚举z个权值最大的森林来枚举z个权值最小的含k条边的反馈边集,从而得到z个权值最小的含k个顶点的反馈顶点集,算法时间复杂度为O(5kn2(logn+k)+3kz(n2logn+z)).     

基于搜索树的平面图支配集算法

许多来自工业应用的优化问题都是NP难问题。确定参数可解FPT作为处理这类问题的另外一种思路,在最近的10多年中受到了广泛的关注。支配集问题是图论中最重要的NP完全的组合优化问题之一,即使对于FPT体系而言,一般图中的支配集问题属于W[2]完全的,意味着不可能设计出复杂度为f(k)no(1)的算法。在本文中,我们考虑在给定的平面图G=(V,E)中参数化支配集问题,给定参数k,看是否存在大小为k的顶点集合支配图中的其他顶点,当把问题限定在平面图上,这个问题属于确定参数可解。本文给出了基于两组归约规则的搜索树算法,通过使用规约技术化简实例,构造搜索树,得到了复杂度为O(8kn)的算法,同时通过相关实验结果显示了归约规则对算法的作用。     

簇图编辑问题的研究进展

簇图编辑问题是一个重要的NP-难问题。作为相关性聚类问题的一个特例,它在计算生物等领域有着重要的应用。参数计算理论出现后,参数化的簇图编辑问题逐渐引起了很多人的注意。介绍了求解簇图编辑问题的近似算法、参数算法和它的一些变形,着重分析了参数化簇图编辑问题核心化和FPT算法的最新结果。最后提出了关于该问题的一些研究方向。     

有向图连通支配集求解算法

定义了有向图指定源点连通支配集问题。借助参数算法中的技术设计了针对该问题的规约规则,通过规约规则的实施来降低原问题的规模;随后又设计了近似算法在规约后的有向图中求出一个较小的连通支配集;最后结合规约规则带来的一些良好特性设计了优化规则,通过优化变换的实施进一步缩减由近似算法求得的连通支配集。不同模型随机图上的模拟实验表明这些规则和算法是有效的。     

3-Set Packing参数化计数问题的复杂性及近似算法

Set Packing参数化计数问题即在一个3-Set Packing实例中统计所有大小为k的不同packing的个数。首先证明了该问题的计算复杂性是#W[1]-难的,表明该问题不大可能存在固定参数可解的精确算法(除非#W[1]=FPT)。然后,通过拓展3-D Matching参数化计数问题的算法对3-Set Packing参数化计数问题提出了一个基于Monte-Carlo自适应覆盖算法和着色技术的随机近似算法。     

广义Kautz有向图GK(3,n)的反馈数的界

对于给定的图G的顶点集的子集F,如果删除F使得剩余子图是无圈子图,则称子集F为图G的反馈点集。研究了广义Kautz有向图GK(d,n)的反馈点集。令f(d,n)表示广义Kautz有向图GK(d,n)的所有反馈集合中顶点个数最少的集合的个数(即广义Kautz有向图GK(d,n)的反馈数),给出了GK(3,n)的反馈数的上界,即 f(3,n)≤n+5n8 － 3n4－ 4n7+3。     

团分划问题的固定参数算法研究

图论中的团分划问题属于NP-完全问题,难以在多项式时间内解决。为此,对团分划问题的固定参数算法进行研究,提出一个针对K4-free图的新归约法则,结合深度限制搜索树技术对K4-free图中的团分划固定参数可解类算法做出改进。实验结果表明,与原算法相比,在稀疏图的情况下改进算法效率提高了30%。     

Labeled Search Trees and Amortized Analysis: Improved Upper Bounds for NP-Hard Problems

A sequence of exact algorithms to solve the Vertex Cover and Maximum Independent Set problems have been proposed in the literature. All these algorithms appeal to a very conservative analysis that considers the size of the search tree, under a worst-case scenario, to derive an upper bound on the running time of the algorithm. In this paper we propose a different approach to analyze the size of the search tree. We use amortized analysis to show how simple algorithms, if analyzed properly, may perform much better than the upper bounds on their running time derived by considering only a worst-case scenario. This approach allows us to present a simple algorithm of running time O(1.194^kk² + n) for the parameterized Vertex Cover problem on degree-3 graphs, and a simple algorithm of running time O(1.1255ⁿ) for the Maximum Independent Set problem on degree-3 graphs. Both algorithms improve the previous best algorithms for the problems.     

Efficient Exact Algorithms through Enumerating Maximal Independent Sets and Other Techniques

We give substantially improved exact exponential-time algorithms for a number of NP-hard problems. These algorithms are obtained using a variety of techniques. These techniques include: obtaining exact algorithms by enumerating maximal independent sets in a graph, obtaining exact algorithms from parameterized algorithms and a variant of the usual branch-and-bound technique which we call the "colored" branch-and-bound technique. These techniques are simple in that they avoid detailed case analyses and yield algorithms that can be easily implemented. We show the power of these techniques by applying them to several NP-hard problems and obtaining new improved upper bounds on the running time. The specific problems that we tackle are: (1) the Odd Cycle Transversal problem in general undirected graphs, (2) the Feedback Vertex Set problem in directed graphs of maximum degree 4, (3) Feedback Arc Set problem in tournaments, (4) the 4-Hitting Set problem and (5) the Minimum Maximal Matching and the Edge Dominating Set problems. The algorithms that we present for these problems are the best known and are a substantial improvement over previous best results. For example, for the Minimum Maximal Matching we give an O^*(1.4425ⁿ) algorithm improving the previous best result of O^*(1.4422^m) [35]. For the Odd Cycle Transversal problem, we give an O^*(1.62ⁿ) algorithm which improves the previous time bound of O^*(1.7724ⁿ) [3].     

Subexponential algorithms for partial cover problems

Partial Cover problems are optimization versions of fundamental and well-studied problems like Vertex Cover and Dominating Set. Here one is interested in covering (or dominating) the maximum number of edges (or vertices) using a given number k of vertices, rather than covering all edges (or vertices). In general graphs, these problems are hard for parameterized complexity classes when parameterized by k. It was recently shown by Amini et al. (2008) [1] that Partial Vertex Cover and Partial Dominating Set are fixed parameter tractable on large classes of sparse graphs, namely H-minor-free graphs, which include planar graphs and graphs of bounded genus. In particular, it was shown that on planar graphs both problems can be solved in time ²O(k)nO(1).During the last decade there has been an extensive study on parameterized subexponential algorithms. In particular, it was shown that the classical Vertex Cover and Dominating Set problems can be solved in subexponential time on H-minor-free graphs. The techniques developed to obtain subexponential algorithms for classical problems do not apply to partial cover problems. It was left as an open problem by Amini et al. (2008) [1] whether there is a subexponential algorithm for Partial Vertex Cover and Partial Dominating Set. In this paper, we answer the question affirmatively by solving both problems in time not only on planar graphs but also on much larger classes of graphs, namely, apex-minor-free graphs. Compared to previously known algorithms for these problems our algorithms are significantly faster and simpler.     

One for the Price of Two: a Unified Approach for Approximating Covering Problems

We present a simple and unified approach for developing and analyzing approximation algorithms for covering problems. We illustrate this on approximation algorithms for the following problems: Vertex Cover, Set Cover, Feedback Vertex Set, Generalized Steiner Forest, and related problems. The main idea can be phrased as follows: iteratively, pay two dollars (at most) to reduce the total optimum by one dollar (at least), so the rate of payment is no more than twice the rate of the optimum reduction. This implies a total payment (i.e., approximation cost) ≤ twice the optimum cost. Our main contribution is based on a formal definition for covering problems, which includes all the above fundamental problems and others. We further extend the Bafna et al. extension of the Local-Ratio theorem. Our extension eventually yields a short generic r -approximation algorithm which can generate most known approximation algorithms for most covering problems. Another extension of the Local-Ratio theorem to randomized algorithms gives a simple proof of Pitt's randomized approximation for Vertex Cover. Using this approach, we develop a modified greedy algorithm, which for Vertex Cover gives an expected performance ratio ≤ 2 . Received September 17, 1997; revised March 5, 1998.     

An O(2<Superscript>O(k)</Superscript>n<Superscript>3</Superscript>) FPT Algorithm for the Undirected Feedback Vertex Set Problem

We describe an algorithm for the Feedback Vertex Set problem on undirected graphs, parameterized by the size k of the feedback vertex set, that runs in time O(c^kn³) where c = 10.567 and n is the number of vertices in the graph. The best previous algorithms were based on the method of bounded search trees, branching on short cycles. The best previous running time of an FPT algorithm for this problem, due to Raman, Saurabh and Subramanian, has a parameter function of the form 2^{O(k log k /log log k)}. Whether an exponentially linear in k FPT algorithm for this problem is possible has been previously noted as a significant challenge. Our algorithm is based on the new FPT technique of iterative compression. Our result holds for a more general form of the problem, where a subset of the vertices may be marked as forbidden to belong to the feedback set. We also establish "exponential optimality" for our algorithm by proving that no FPT algorithm with a parameter function of the form O(2^o(k)) is possible, unless there is an unlikely collapse of parameterized complexity classes, namely FPT = M[1].     

Feedback arc set problem in bipartite tournaments

In this paper we give ratio 4 deterministic and randomized approximation algorithms for the Feedback Arc Set problem in bipartite tournaments. We also generalize these results to give a factor 4 deterministic approximation algorithm for Feedback Arc Set problem in multipartite tournaments.     

A linear time algorithm for the minimum Weighted Feedback Vertex Set on diamonds

Given an undirected and vertex weighted graph G, the Weighted Feedback Vertex Problem (WFVP) consists in finding a subset F⊆V of vertices of minimum weight such that each cycle in G contains at least one vertex in F. The WFVP on general graphs is known to be NP-hard. In this paper we introduce a new class of graphs, namely the diamond graphs, and give a linear time algorithm to solve WFVP on it.     

Parameterized algorithms for feedback set problems and their duals in tournaments

The parameterized feedback vertex (arc) set problem is to find whether there are k vertices (arcs) in a given graph whose removal makes the graph acyclic. The parameterized complexity of this problem in general directed graphs is a long standing open problem. We investigate the problems on tournaments, a well studied class of directed graphs. We consider both weighted and unweighted versions.