A fixed-parameter algorithm for minimum quartet inconsistency

Given n taxa, exactly one topology for every subset of four taxa, and a positive integer k (the parameter), the Minimum Quartet Inconsistency (MQI) problem is the question whether we can find an evolutionary tree inducing a set of quartet topologies that differs from the given set in only k quartet topologies. The more general problem where we are not necessarily given a topology for every subset of four taxa appears to be fixed-parameter intractable. For MQI, however, which is also NP-complete, we can compute the required tree in time O(4^kn+n⁴). This means that the problem is fixed-parameter tractable and that in the case of a small number k of “errors” the tree reconstruction can be done efficiently. In particular, for minimal k, our algorithm can produce all solutions that resolve k errors. Additionally, we discuss significant heuristic improvements. Experiments underline the practical relevance of our solutions.     

Kernels for below-upper-bound parameterizations of the hitting set and directed dominating set problems

In the Hitting Set problem, we are given a collection F of subsets of a ground set V and an integer p, and asked whether V has a p-element subset that intersects each set in F. We consider two parameterizations of Hitting Set below tight upper bounds, p=m−k and p=n−k. In both cases k is the parameter. We prove that the first parameterization is fixed-parameter tractable, but has no polynomial kernel unless coNP ⊆ NP/poly. The second parameterization is W[1]-complete, but the introduction of an additional parameter, the degeneracy of the hypergraph H=(V,F), makes the problem not only fixed-parameter tractable, but also one with a linear kernel. Here the degeneracy of H=(V,F) is the minimum integer d such that for each X⊂V the hypergraph with vertex set V?X and edge set containing all edges of F without vertices in X, has a vertex of degree at most d.In Nonblocker (Directed Nonblocker), we are given an undirected graph (a directed graph) G on n vertices and an integer k, and asked whether G has a set X of n−k vertices such that for each vertex y∉X there is an edge (arc) from a vertex in X to y. Nonblocker can be viewed as a special case of Directed Nonblocker (replace an undirected graph by a symmetric digraph). Dehne et al. (Proc. SOFSEM 2006) proved that Nonblocker has a linear-order kernel. We obtain a linear-order kernel for Directed Nonblocker.     

Deciding k-colorability in expected polynomial time

For every fixed k?3 we describe an algorithm for deciding k-colorability, whose expected running time in polynomial in the probability space G(n,p) of random graphs as long as the edge probability p=p(n) satisfies p(n)?C/n, with C=C(k) being a sufficiently large constant.     

Clustering Large Graphs via the Singular Value Decomposition

We consider the problem of partitioning a set of m points in the n-dimensional Euclidean space into k clusters (usually m and n are variable, while k is fixed), so as to minimize the sum of squared distances between each point and its cluster center. This formulation is usually the objective of the k-means clustering algorithm (Kanungo et al. (2000)). We prove that this problem in NP-hard even for k = 2, and we consider a continuous relaxation of this discrete problem: find the k-dimensional subspace V that minimizes the sum of squared distances to V of the m points. This relaxation can be solved by computing the Singular Value Decomposition (SVD) of the m × n matrix A that represents the m points; this solution can be used to get a 2-approximation algorithm for the original problem. We then argue that in fact the relaxation provides a generalized clustering which is useful in its own right. Finally, we show that the SVD of a random submatrix—chosen according to a suitable probability distribution—of a given matrix provides an approximation to the SVD of the whole matrix, thus yielding a very fast randomized algorithm. We expect this algorithm to be the main contribution of this paper, since it can be applied to problems of very large size which typically arise in modern applications.     

Compression-based fixed-parameter algorithms for feedback vertex set and edge bipartization

We show that the NP-complete Feedback Vertex Set problem, which asks for the smallest set of vertices to remove from a graph to destroy all cycles, is deterministically solvable in O(ck⋅m) time. Here, m denotes the number of graph edges, k denotes the size of the feedback vertex set searched for, and c is a constant. We extend this to an algorithm enumerating all solutions in O(dk⋅m) time for a (larger) constant d. As a further result, we present a fixed-parameter algorithm with runtime O(k²⋅m²) for the NP-complete Edge Bipartization problem, which asks for at most k edges to remove from a graph to make it bipartite.     

Fixed-Parameter Approximation: Conceptual Framework and Approximability Results

The notion of fixed-parameter approximation is introduced to investigate the approximability of optimization problems within the framework of fixed-parameter computation. This work partially aims at enhancing the world of fixed-parameter computation in parallel with the conventional theory of computation that includes both exact and approximate computations. In particular, it is proved that fixed-parameter approximability is closely related to the approximation of small-cost solutions in polynomial time. It is also demonstrated that many fixed-parameter intractable problems are not fixed-parameter approximable. On the other hand, fixed-parameter approximation appears to be a viable approach to solving some inapproximable yet important optimization problems. For instance, all problems in the class MAX SNP admit fixed-parameter approximation schemes in time O(2 ^{O((1−ε/O(1))k)} p(n)) for any small ε>0.     

Constant ratio fixed-parameter approximation of the edge multicut problem

The input of the Edge Multicut problem consists of an undirected graph G and pairs of terminals {s₁,t₁},…,{sm,tm}; the task is to remove a minimum set of edges such that si and ti are disconnected for every 1?i?m. The parameterized complexity of the problem, parameterized by the maximum number k of edges that are allowed to be removed, is currently open. The main result of the paper is a parameterized 2-approximation algorithm: in time f(k)⋅nO(1), we can either find a solution of size 2k or correctly conclude that there is no solution of size k.The proposed algorithm is based on a transformation of the Edge Multicut problem into a variant of the parameterized Max-2SAT problem, where the parameter is related to the number of clauses that are not satisfied. It follows from previous results that the latter problem can be 2-approximated in a fixed-parameter time; on the other hand, we show here that it is W[1]-hard. Thus the additional contribution of the present paper is introducing the first natural W[1]-hard problem that is constant-ratio fixed-parameter approximable.     

The densest hemisphere problem

Given a set K of n points on the unit sphere S^d in d-dimensional Euclidean space, a hemisphere of S^d is densest if it contains a largest subset of K. In this paper we consider the problem of determining a densest hemisphere and present the following complementary results: (i) a discretized version of the original problem, restated as a feasibility question, is NP-complete when both n and d are arbitrary; (ii) when the number d of dimensions is fixed, there exists a polynomial time algorithm which solves the problem in time O(n_d?1 log n) on a random access machine with unit cost arithmetic operations.     

随机可满足实例集上警示传播算法的收敛性

信息传播算法在求解随机kSAT问题时有惊人的效果,难解区域变窄.对于这种现象,至今缺少系统的理论解释.警示传播(warning propagation,简称WP)算法是一种基础的信息传播算法,为有效分析WP算法在随机kCNF公式上的收敛性,给出了随机kCNF公式因子图上圈存在的相变点.在随机kCNF公式产生模型G(n,k,p)中,取k=3,p=d/n2,因子图中圈存在的相变点为p=1/8n2.当d＜1/8时,因子图中开始出现圈,且每个连通分支至多有一个圈,因子图中含圈的连通分支的数目以及圈的长度均与n无关.因此,因子图是由森林和一些含有唯一圈的连通分支构成.证明了WP算法在这些实例集上高概率收敛,并且给出了算法的迭代步数为O(logn+s),其中,s为连通分支的大小.     

Approximation Schemes for Packing Splittable Items with Cardinality Constraints

We continue the study of bin packing with splittable items and cardinality constraints. In this problem, a set of n items must be packed into as few bins as possible. Items may be split, but each bin may contain at most?k (parts of) items, where k is some given parameter. Complicating the problem further is the fact that items may be larger than?1, which is the size of a bin. The problem is known to be strongly NP-hard for any fixed value of?k. We essentially close this problem by providing an efficient polynomial-time approximation scheme (EPTAS) for most of its versions. Namely, we present an efficient polynomial time approximation scheme for k=o(n). A?PTAS for k=Θ(n) does not exist unless P = NP. Additionally, we present dual approximation schemes for k=2 and for constant values of?k. Thus we show that for any ε>0, it is possible to pack the items into the optimal number of bins in polynomial time, if the algorithm may use bins of size 1+ε.     

Note on Max Lin-2 above Average

In the Max Lin-2 problem we are given a system S of m linear equations in n variables over F₂ in which equation j is assigned a positive integral weight wj for each j. We wish to find an assignment of values to the variables which maximizes the total weight of satisfied equations. This problem generalizes Max Cut. The expected weight of satisfied equations is W/2, where W=w₁+?+wm; W/2 is a tight lower bound on the optimal solution of Max Lin-2.Mahajan et al. (Parameterizing above or below guaranteed values, J. Comput. Syst. Sci. 75 (2009) 137-153) stated the following parameterized version of Max Lin-2: decide whether there is an assignment of values to the variables that satisfies equations of total weight at least W/2+k, where k is the parameter. They asked whether this parameterized problem is fixed-parameter tractable, i.e., can be solved in time f(k)(nm)^O(1), where f(k) is an arbitrary computable function in k only. Their question remains open, but using some probabilistic inequalities and, in one case, a Fourier analysis inequality, Gutin et al. (A probabilistic approach to problems parameterized above tight lower bound, in: Proc. IWPEC'09, in: Lect. Notes Comput. Sci., vol. 5917, 2009, pp. 234-245) proved that the problem is fixed-parameter tractable in three special cases.In this paper we significantly extend two of the three special cases using only tools from combinatorics. We show that one of our results can be used to obtain a combinatorial proof that another problem from Mahajan et al. (Parameterizing above or below guaranteed values, J. Comput. Syst. Sci. 75 (2009) 137-153), Max r-SAT above Average, is fixed-parameter tractable for each r?2. Note that Max r-SAT above Average has been already shown to be fixed-parameter tractable by Alon et al. (Solving MAX-r-SAT above a tight lower bound, in: Proc. SODA 2010, pp. 511-517), but the paper used the approach of Gutin et al. (A probabilistic approach to problems parameterized above tight lower bound, in: Proc. IWPEC'09, in: Lect. Notes Comput. Sci., vol. 5917, 2009, pp. 234-245).     

取定s的严格d-正则随机(3,2s)-SAT问题的可满足临界

3-CNF公式的随机难解实例生成对于揭示3-SAT问题的难解实质和设计满足性测试的有效算法有着重要意义.对于整数k>2和s>0,如果在一个k-CNF公式中每个变量正负出现次数均为s,则称该公式是严格正则（k,2s）-CNF公式.受严格正则（k,2s）-CNF公式的结构特征启发,提出每个变量正负出现次数之差的绝对值均为d的严格d-正则（k,2s）-CNF公式,并使用新提出的SDRRK2S模型生成严格d-正则随机（k,2s）-CNF公式.取定整数5<s<11,模拟实验显示,严格d-正则随机（3,2s）-SAT问题存在SAT-UNSAT相变现象和HARD-EASY相变现象.因此,立足于3-CNF公式的随机难解实例生成,研究了严格d-正则随机（3,2s）-SAT问题在s取定时的可满足临界.通过构造一个特殊随机实验和使用一阶矩方法,得到了严格d-正则随机（3,2s）-SAT问题在s取定时可满足临界值的一个下界.模拟实验结果验证了理论证明所得下界的正确性.     

Learning large-alphabet and analog circuits with value injection queries

We consider the problem of learning an acyclic discrete circuit with n wires, fan-in bounded by k and alphabet size s using value injection queries. For the class of transitively reduced circuits, we develop the Distinguishing Paths Algorithm, that learns such a circuit using (ns) ^O(k) value injection queries and time polynomial in the number of queries. We describe a generalization of the algorithm to the class of circuits with shortcut width bounded by b that uses (ns) ^O(k+b) value injection queries. Both algorithms use value injection queries that fix only O(kd) wires, where d is the depth of the target circuit. We give a reduction showing that without such restrictions on the topology of the circuit, the learning problem may be computationally intractable when s=n ^Θ(1), even for circuits of depth O(log?n). We then apply our large-alphabet learning algorithms to the problem of approximate learning of analog circuits whose gate functions satisfy a Lipschitz condition. Finally, we consider models in which behavioral equivalence queries are also available, and extend and improve the learning algorithms of (Angluin in Proceedings of the Thirty-Eighth Annual ACM Symposium on Theory of Computing, pp. 584–593, 2006) to handle general classes of gate functions that are polynomial time learnable from counterexamples.     

A comparative runtime analysis of heuristic algorithms for satisfiability problems

The satisfiability problem is a basic core NP-complete problem. In recent years, a lot of heuristic algorithms have been developed to solve this problem, and many experiments have evaluated and compared the performance of different heuristic algorithms. However, rigorous theoretical analysis and comparison are rare. This paper analyzes and compares the expected runtime of three basic heuristic algorithms: RandomWalk, (1+1) EA, and hybrid algorithm. The runtime analysis of these heuristic algorithms on two 2-SAT instances shows that the expected runtime of these heuristic algorithms can be exponential time or polynomial time. Furthermore, these heuristic algorithms have their own advantages and disadvantages in solving different SAT instances. It also demonstrates that the expected runtime upper bound of RandomWalk on arbitrary k-SAT (k?3) is O(n(k−1)), and presents a k-SAT instance that has Θ(n(k−1)) expected runtime bound.     

Random Walks,Bisections and Gossiping in Circulant Graphs

Circulant graphs are regular graphs based on Cayley graphs defined on the Abelian group \(\mathbb{Z}_{n}\) . They are popular network topologies that arise in distributed computing. Using number theoretical tools, we first prove two main results for random directed k-regular circulant graphs with n vertices, when n is sufficiently large and k is fixed. First, for any fixed ε>0, n=p prime and L≥p ^1/k (logp)^1+1/k+ε , walks of length at most L terminate at every vertex with asymptotically the same probability. Second, for any n, there is a polynomial time algorithm that for almost all undirected 2r-regular circulant graphs finds a vertex bisector and an edge bisector, both of size less than n ^1?1/r+o(1). We then prove that the latter result also holds for all (rather than for almost all) 2r-regular circulant graphs with n=p, prime, vertices, while, in general, it does not hold for composite n. Using the bisection results, we provide lower bounds on the number of rounds required by any gossiping algorithms for any n. We introduce generic distributed algorithms to solve the gossip problem in any circulant graphs. We illustrate the efficiency of these algorithms by giving nearly matching upper bounds of the number of rounds required by these algorithms in the vertex-disjoint and the edge-disjoint paths communication models in particular circulant graphs.     

The Parameterized Complexity of Stabbing Rectangles

The NP-complete geometric covering problem Rectangle Stabbing is defined as follows: Given a set R of axis-parallel rectangles in the plane, a set L of horizontal and vertical lines in the plane, and a positive integer k, select at most k of the lines such that every rectangle is intersected by at least one of the selected lines. While it is known that the problem can be approximated in polynomial time within a factor of two, its parameterized complexity with respect to the parameter k was open so far. Giving two fixed-parameter reductions, one from the W[1]-complete problem Multicolored Clique and one to the W[1]-complete problem Short Turing Machine Acceptance, we prove that Rectangle Stabbing is W[1]-complete with respect to the parameter k, which in particular means that there is no hope for an algorithm running in f(k)?|R∪L| ^O(1) time. Our reductions also show the W[1]-completeness of the more general problem Set Cover on instances that “almost have the consecutive-ones property”, that is, on instances whose matrix representation has at most two blocks of 1s per row. We also show that the special case of Rectangle Stabbing where all rectangles are squares of the same size is W[1]-hard. The case where the input consists of non-overlapping rectangles was open for some time and has recently been shown to be fixed-parameter tractable (Heggernes et al., Fixed-parameter algorithms for cochromatic number and disjoint rectangle stabbing, 2009). By giving an algorithm running in (2k) ^k ?|R∪L| ^O(1) time, we show that Rectangle Stabbing is fixed-parameter tractable in the still NP-hard case where both these restrictions apply, that is, in the case of disjoint squares of the same size. This algorithm is faster than the one in Heggernes et al. (Fixed-parameter algorithms for cochromatic number and disjoint rectangle stabbing, 2009) for the disjoint rectangles case. Moreover, we show fixed-parameter tractability for the restrictions where the rectangles have bounded width or height or where each horizontal line intersects only a bounded number of rectangles.     

Spanners of bounded degree graphs

A k-spanner of a graph G is a spanning subgraph of G in which the distance between any pair of vertices is at most k times the distance in G. We prove that for fixed k,w, the problem of deciding if a given graph has a k-spanner of treewidth w is fixed-parameter tractable on graphs of bounded degree. In particular, this implies that finding a k-spanner that is a tree (a tree k-spanner) is fixed-parameter tractable on graphs of bounded degree. In contrast, we observe that if the graph has only one vertex of unbounded degree, then Treek-Spanner is NP-complete for k?4.     

Parameterized algorithm for eternal vertex cover

In this paper we initiate the study of a “dynamic” variant of the classical Vertex Cover problem, the Eternal Vertex Cover problem introduced by Klostermeyer and Mynhardt, from the perspective of parameterized algorithms. This problem consists in placing a minimum number of guards on the vertices of a graph such that these guards can protect the graph from any sequence of attacks on its edges. In response to an attack, each guard is allowed either to stay in his vertex, or to move to a neighboring vertex. However, at least one guard has to fix the attacked edge by moving along it. The other guards may move to reconfigure and prepare for the next attack. Thus at every step the vertices occupied by guards form a vertex cover. We show that the problem admits a kernel of size k⁴(k+1)+2k, which shows that the problem is fixed parameter tractable when parameterized by the number of available guards k. Finally, we also provide an algorithm with running time O(²O(k²)+nm) for Eternal Vertex Cover, where n is the number of vertices and m the number of edges of the input graph. In passing we also observe that Eternal Vertex Cover is NP-hard, yet it has a polynomial time 2-approximation algorithm.     

Swarm intelligence approaches for multidepot salesmen problems with load balancing

Given a set of n cities and m salesmen stationed at d depots, the fixed destination multidepot salesmen problem consists in finding tours for all the salesmen which start and end at their corresponding fixed depots such that each city is visited exactly once by one salesman only, the workload among salesmen is balanced and the total distance traveled by all the salesmen is minimized. In this paper, we have proposed two swarm intelligence approaches for this problem. The first approach is based on artificial bee colony algorithm, whereas the latter approach is based on invasive weed optimization algorithm. Computational results on instances derived from TSPLIB show the effectiveness of our proposed approaches over other state-of-the-art approaches for this problem.     

On finding short resolution refutations and small unsatisfiable subsets

We consider the parameterized problems of whether a given set of clauses can be refuted within k resolution steps, and whether a given set of clauses contains an unsatisfiable subset of size at most k  . We show that both problems are complete for the class W[1]$\mathrm{W}[1]$, the first level of the W-hierarchy of fixed-parameter intractable problems. Our results remain true if restricted to 3-SAT instances and/or to various restricted versions of resolution including tree-like resolution, input resolution, and read-once resolution. Applying a metatheorem of Frick and Grohe, we show that, restricted to classes of sets of clauses of locally bounded treewidth, the considered problems are fixed-parameter tractable. For example, the problems are fixed-parameter tractable for planar CNF formulas.