4,118 research outputs found

    Tractable Combinations of Global Constraints

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    We study the complexity of constraint satisfaction problems involving global constraints, i.e., special-purpose constraints provided by a solver and represented implicitly by a parametrised algorithm. Such constraints are widely used; indeed, they are one of the key reasons for the success of constraint programming in solving real-world problems. Previous work has focused on the development of efficient propagators for individual constraints. In this paper, we identify a new tractable class of constraint problems involving global constraints of unbounded arity. To do so, we combine structural restrictions with the observation that some important types of global constraint do not distinguish between large classes of equivalent solutions.Comment: To appear in proceedings of CP'13, LNCS 8124. arXiv admin note: text overlap with arXiv:1307.179

    Tractable Optimization Problems through Hypergraph-Based Structural Restrictions

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    Several variants of the Constraint Satisfaction Problem have been proposed and investigated in the literature for modelling those scenarios where solutions are associated with some given costs. Within these frameworks computing an optimal solution is an NP-hard problem in general; yet, when restricted over classes of instances whose constraint interactions can be modelled via (nearly-)acyclic graphs, this problem is known to be solvable in polynomial time. In this paper, larger classes of tractable instances are singled out, by discussing solution approaches based on exploiting hypergraph acyclicity and, more generally, structural decomposition methods, such as (hyper)tree decompositions

    Achieving New Upper Bounds for the Hypergraph Duality Problem through Logic

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    The hypergraph duality problem DUAL is defined as follows: given two simple hypergraphs G\mathcal{G} and H\mathcal{H}, decide whether H\mathcal{H} consists precisely of all minimal transversals of G\mathcal{G} (in which case we say that G\mathcal{G} is the dual of H\mathcal{H}). This problem is equivalent to deciding whether two given non-redundant monotone DNFs are dual. It is known that non-DUAL, the complementary problem to DUAL, is in GC(log2n,PTIME)\mathrm{GC}(\log^2 n,\mathrm{PTIME}), where GC(f(n),C)\mathrm{GC}(f(n),\mathcal{C}) denotes the complexity class of all problems that after a nondeterministic guess of O(f(n))O(f(n)) bits can be decided (checked) within complexity class C\mathcal{C}. It was conjectured that non-DUAL is in GC(log2n,LOGSPACE)\mathrm{GC}(\log^2 n,\mathrm{LOGSPACE}). In this paper we prove this conjecture and actually place the non-DUAL problem into the complexity class GC(log2n,TC0)\mathrm{GC}(\log^2 n,\mathrm{TC}^0) which is a subclass of GC(log2n,LOGSPACE)\mathrm{GC}(\log^2 n,\mathrm{LOGSPACE}). We here refer to the logtime-uniform version of TC0\mathrm{TC}^0, which corresponds to FO(COUNT)\mathrm{FO(COUNT)}, i.e., first order logic augmented by counting quantifiers. We achieve the latter bound in two steps. First, based on existing problem decomposition methods, we develop a new nondeterministic algorithm for non-DUAL that requires to guess O(log2n)O(\log^2 n) bits. We then proceed by a logical analysis of this algorithm, allowing us to formulate its deterministic part in FO(COUNT)\mathrm{FO(COUNT)}. From this result, by the well known inclusion TC0LOGSPACE\mathrm{TC}^0\subseteq\mathrm{LOGSPACE}, it follows that DUAL belongs also to DSPACE[log2n]\mathrm{DSPACE}[\log^2 n]. Finally, by exploiting the principles on which the proposed nondeterministic algorithm is based, we devise a deterministic algorithm that, given two hypergraphs G\mathcal{G} and H\mathcal{H}, computes in quadratic logspace a transversal of G\mathcal{G} missing in H\mathcal{H}.Comment: Restructured the presentation in order to be the extended version of a paper that will shortly appear in SIAM Journal on Computin

    Hypergraph Acyclicity and Propositional Model Counting

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    We show that the propositional model counting problem #SAT for CNF- formulas with hypergraphs that allow a disjoint branches decomposition can be solved in polynomial time. We show that this class of hypergraphs is incomparable to hypergraphs of bounded incidence cliquewidth which were the biggest class of hypergraphs for which #SAT was known to be solvable in polynomial time so far. Furthermore, we present a polynomial time algorithm that computes a disjoint branches decomposition of a given hypergraph if it exists and rejects otherwise. Finally, we show that some slight extensions of the class of hypergraphs with disjoint branches decompositions lead to intractable #SAT, leaving open how to generalize the counting result of this paper
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