3,000 research outputs found

    Longest Common Separable Pattern between Permutations

    Get PDF
    In this article, we study the problem of finding the longest common separable pattern between several permutations. We give a polynomial-time algorithm when the number of input permutations is fixed and show that the problem is NP-hard for an arbitrary number of input permutations even if these permutations are separable. On the other hand, we show that the NP-hard problem of finding the longest common pattern between two permutations cannot be approximated better than within a ratio of sqrtOptsqrt{Opt} (where OptOpt is the size of an optimal solution) when taking common patterns belonging to pattern-avoiding classes of permutations.Comment: 15 page

    Zero forcing number, constrained matchings and strong structural controllability

    Full text link
    The zero forcing number is a graph invariant introduced to study the minimum rank of the graph. In 2008, Aazami proved the NP-hardness of computing the zero forcing number of a simple undirected graph. We complete this NP-hardness result by showing that the non-equivalent problem of computing the zero forcing number of a directed graph allowing loops is also NP-hard. The rest of the paper is devoted to the strong controllability of a networked system. This kind of controllability takes into account only the structure of the interconnection graph, but not the interconnection strengths along the edges. We provide a necessary and sufficient condition in terms of zero forcing sets for the strong controllability of a system whose underlying graph is a directed graph allowing loops. Moreover, we explain how our result differs from a recent related result discovered by Monshizadeh et al. Finally, we show how to solve the problem of finding efficiently a minimum-size input set for the strong controllability of a self-damped system with a tree-structure.Comment: Submitted as a journal paper in May 201

    Inapproximability of maximal strip recovery

    Get PDF
    In comparative genomic, the first step of sequence analysis is usually to decompose two or more genomes into syntenic blocks that are segments of homologous chromosomes. For the reliable recovery of syntenic blocks, noise and ambiguities in the genomic maps need to be removed first. Maximal Strip Recovery (MSR) is an optimization problem proposed by Zheng, Zhu, and Sankoff for reliably recovering syntenic blocks from genomic maps in the midst of noise and ambiguities. Given dd genomic maps as sequences of gene markers, the objective of \msr{d} is to find dd subsequences, one subsequence of each genomic map, such that the total length of syntenic blocks in these subsequences is maximized. For any constant d2d \ge 2, a polynomial-time 2d-approximation for \msr{d} was previously known. In this paper, we show that for any d2d \ge 2, \msr{d} is APX-hard, even for the most basic version of the problem in which all gene markers are distinct and appear in positive orientation in each genomic map. Moreover, we provide the first explicit lower bounds on approximating \msr{d} for all d2d \ge 2. In particular, we show that \msr{d} is NP-hard to approximate within Ω(d/logd)\Omega(d/\log d). From the other direction, we show that the previous 2d-approximation for \msr{d} can be optimized into a polynomial-time algorithm even if dd is not a constant but is part of the input. We then extend our inapproximability results to several related problems including \cmsr{d}, \gapmsr{\delta}{d}, and \gapcmsr{\delta}{d}.Comment: A preliminary version of this paper appeared in two parts in the Proceedings of the 20th International Symposium on Algorithms and Computation (ISAAC 2009) and the Proceedings of the 4th International Frontiers of Algorithmics Workshop (FAW 2010

    Complexity of Token Swapping and its Variants

    Full text link
    In the Token Swapping problem we are given a graph with a token placed on each vertex. Each token has exactly one destination vertex, and we try to move all the tokens to their destinations, using the minimum number of swaps, i.e., operations of exchanging the tokens on two adjacent vertices. As the main result of this paper, we show that Token Swapping is W[1]W[1]-hard parameterized by the length kk of a shortest sequence of swaps. In fact, we prove that, for any computable function ff, it cannot be solved in time f(k)no(k/logk)f(k)n^{o(k / \log k)} where nn is the number of vertices of the input graph, unless the ETH fails. This lower bound almost matches the trivial nO(k)n^{O(k)}-time algorithm. We also consider two generalizations of the Token Swapping, namely Colored Token Swapping (where the tokens have different colors and tokens of the same color are indistinguishable), and Subset Token Swapping (where each token has a set of possible destinations). To complement the hardness result, we prove that even the most general variant, Subset Token Swapping, is FPT in nowhere-dense graph classes. Finally, we consider the complexities of all three problems in very restricted classes of graphs: graphs of bounded treewidth and diameter, stars, cliques, and paths, trying to identify the borderlines between polynomial and NP-hard cases.Comment: 23 pages, 7 Figure

    Counting Houses of Pareto Optimal Matchings in the House Allocation Problem

    Get PDF
    Let A,BA,B with A=m|A| = m and B=nm|B| = n\ge m be two sets. We assume that every element aAa\in A has a reference list over all elements from BB. We call an injective mapping τ\tau from AA to BB a matching. A blocking coalition of τ\tau is a subset AA' of AA such that there exists a matching τ\tau' that differs from τ\tau only on elements of AA', and every element of AA' improves in τ\tau', compared to τ\tau according to its preference list. If there exists no blocking coalition, we call the matching τ\tau an exchange stable matching (ESM). An element bBb\in B is reachable if there exists an exchange stable matching using bb. The set of all reachable elements is denoted by EE^*. We show Ei=1,,mmi=Θ(mlogm).|E^*| \leq \sum_{i = 1,\ldots, m}{\left\lfloor\frac{m}{i}\right\rfloor} = \Theta(m\log m). This is asymptotically tight. A set EBE\subseteq B is reachable (respectively exactly reachable) if there exists an exchange stable matching τ\tau whose image contains EE as a subset (respectively equals EE). We give bounds for the number of exactly reachable sets. We find that our results hold in the more general setting of multi-matchings, when each element aa of AA is matched with a\ell_a elements of BB instead of just one. Further, we give complexity results and algorithms for corresponding algorithmic questions. Finally, we characterize unavoidable elements, i.e., elements of BB that are used by all ESM's. This yields efficient algorithms to determine all unavoidable elements.Comment: 24 pages 2 Figures revise
    corecore