3,286 research outputs found

    Structure of conflict graphs in constraint alignment problems and algorithms

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    We consider the constrained graph alignment problem which has applications in biological network analysis. Given two input graphs G1=(V1,E1),G2=(V2,E2)G_1=(V_1,E_1), G_2=(V_2,E_2), a pair of vertex mappings induces an {\it edge conservation} if the vertex pairs are adjacent in their respective graphs. %In general terms The goal is to provide a one-to-one mapping between the vertices of the input graphs in order to maximize edge conservation. However the allowed mappings are restricted since each vertex from V1V_1 (resp. V2V_2) is allowed to be mapped to at most m1m_1 (resp. m2m_2) specified vertices in V2V_2 (resp. V1V_1). Most of results in this paper deal with the case m2=1m_2=1 which attracted most attention in the related literature. We formulate the problem as a maximum independent set problem in a related {\em conflict graph} and investigate structural properties of this graph in terms of forbidden subgraphs. We are interested, in particular, in excluding certain wheals, fans, cliques or claws (all terms are defined in the paper), which corresponds in excluding certain cycles, paths, cliques or independent sets in the neighborhood of each vertex. Then, we investigate algorithmic consequences of some of these properties, which illustrates the potential of this approach and raises new horizons for further works. In particular this approach allows us to reinterpret a known polynomial case in terms of conflict graph and to improve known approximation and fixed-parameter tractability results through efficiently solving the maximum independent set problem in conflict graphs. Some of our new approximation results involve approximation ratios that are function of the optimal value, in particular its square root; this kind of results cannot be achieved for maximum independent set in general graphs.Comment: 22 pages, 6 figure

    The complexity of acyclic conjunctive queries revisited

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    In this paper, we consider first-order logic over unary functions and study the complexity of the evaluation problem for conjunctive queries described by such kind of formulas. A natural notion of query acyclicity for this language is introduced and we study the complexity of a large number of variants or generalizations of acyclic query problems in that context (Boolean or not Boolean, with or without inequalities, comparisons, etc...). Our main results show that all those problems are \textit{fixed-parameter linear} i.e. they can be evaluated in time f(∣Q∣).∣db∣.∣Q(db)∣f(|Q|).|\textbf{db}|.|Q(\textbf{db})| where ∣Q∣|Q| is the size of the query QQ, ∣db∣|\textbf{db}| the database size, ∣Q(db)∣|Q(\textbf{db})| is the size of the output and ff is some function whose value depends on the specific variant of the query problem (in some cases, ff is the identity function). Our results have two kinds of consequences. First, they can be easily translated in the relational (i.e., classical) setting. Previously known bounds for some query problems are improved and new tractable cases are then exhibited. Among others, as an immediate corollary, we improve a result of \~\cite{PapadimitriouY-99} by showing that any (relational) acyclic conjunctive query with inequalities can be evaluated in time f(∣Q∣).∣db∣.∣Q(db)∣f(|Q|).|\textbf{db}|.|Q(\textbf{db})|. A second consequence of our method is that it provides a very natural descriptive approach to the complexity of well-known algorithmic problems. A number of examples (such as acyclic subgraph problems, multidimensional matching, etc...) are considered for which new insights of their complexity are given.Comment: 30 page

    Understanding the complexity of #SAT using knowledge compilation

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    Two main techniques have been used so far to solve the #P-hard problem #SAT. The first one, used in practice, is based on an extension of DPLL for model counting called exhaustive DPLL. The second approach, more theoretical, exploits the structure of the input to compute the number of satisfying assignments by usually using a dynamic programming scheme on a decomposition of the formula. In this paper, we make a first step toward the separation of these two techniques by exhibiting a family of formulas that can be solved in polynomial time with the first technique but needs an exponential time with the second one. We show this by observing that both techniques implicitely construct a very specific boolean circuit equivalent to the input formula. We then show that every beta-acyclic formula can be represented by a polynomial size circuit corresponding to the first method and exhibit a family of beta-acyclic formulas which cannot be represented by polynomial size circuits corresponding to the second method. This result shed a new light on the complexity of #SAT and related problems on beta-acyclic formulas. As a byproduct, we give new handy tools to design algorithms on beta-acyclic hypergraphs

    Parameterized Directed kk-Chinese Postman Problem and kk Arc-Disjoint Cycles Problem on Euler Digraphs

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    In the Directed kk-Chinese Postman Problem (kk-DCPP), we are given a connected weighted digraph GG and asked to find kk non-empty closed directed walks covering all arcs of GG such that the total weight of the walks is minimum. Gutin, Muciaccia and Yeo (Theor. Comput. Sci. 513 (2013) 124--128) asked for the parameterized complexity of kk-DCPP when kk is the parameter. We prove that the kk-DCPP is fixed-parameter tractable. We also consider a related problem of finding kk arc-disjoint directed cycles in an Euler digraph, parameterized by kk. Slivkins (ESA 2003) showed that this problem is W[1]-hard for general digraphs. Generalizing another result by Slivkins, we prove that the problem is fixed-parameter tractable for Euler digraphs. The corresponding problem on vertex-disjoint cycles in Euler digraphs remains W[1]-hard even for Euler digraphs

    On the fixed-parameter tractability of the maximum connectivity improvement problem

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    In the Maximum Connectivity Improvement (MCI) problem, we are given a directed graph G=(V,E)G=(V,E) and an integer BB and we are asked to find BB new edges to be added to GG in order to maximize the number of connected pairs of vertices in the resulting graph. The MCI problem has been studied from the approximation point of view. In this paper, we approach it from the parameterized complexity perspective in the case of directed acyclic graphs. We show several hardness and algorithmic results with respect to different natural parameters. Our main result is that the problem is W[2]W[2]-hard for parameter BB and it is FPT for parameters ∣V∣−B|V| - B and ν\nu, the matching number of GG. We further characterize the MCI problem with respect to other complementary parameters.Comment: 15 pages, 1 figur
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