1,052 research outputs found

    Incremental complexity of a bi-objective hypergraph transversal problem

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    The hypergraph transversal problem has been intensively studied, from both a theoretical and a practical point of view. In particular , its incremental complexity is known to be quasi-polynomial in general and polynomial for bounded hypergraphs. Recent applications in computational biology however require to solve a generalization of this problem, that we call bi-objective transversal problem. The instance is in this case composed of a pair of hypergraphs (A, B), and the aim is to find minimal sets which hit all the hyperedges of A while intersecting a minimal set of hyperedges of B. In this paper, we formalize this problem, link it to a problem on monotone boolean \land -- \lor formulae of depth 3 and study its incremental complexity

    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

    Simultaneous Embeddability of Two Partitions

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    We study the simultaneous embeddability of a pair of partitions of the same underlying set into disjoint blocks. Each element of the set is mapped to a point in the plane and each block of either of the two partitions is mapped to a region that contains exactly those points that belong to the elements in the block and that is bounded by a simple closed curve. We establish three main classes of simultaneous embeddability (weak, strong, and full embeddability) that differ by increasingly strict well-formedness conditions on how different block regions are allowed to intersect. We show that these simultaneous embeddability classes are closely related to different planarity concepts of hypergraphs. For each embeddability class we give a full characterization. We show that (i) every pair of partitions has a weak simultaneous embedding, (ii) it is NP-complete to decide the existence of a strong simultaneous embedding, and (iii) the existence of a full simultaneous embedding can be tested in linear time.Comment: 17 pages, 7 figures, extended version of a paper to appear at GD 201

    Combinatorics and geometry of finite and infinite squaregraphs

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    Squaregraphs were originally defined as finite plane graphs in which all inner faces are quadrilaterals (i.e., 4-cycles) and all inner vertices (i.e., the vertices not incident with the outer face) have degrees larger than three. The planar dual of a finite squaregraph is determined by a triangle-free chord diagram of the unit disk, which could alternatively be viewed as a triangle-free line arrangement in the hyperbolic plane. This representation carries over to infinite plane graphs with finite vertex degrees in which the balls are finite squaregraphs. Algebraically, finite squaregraphs are median graphs for which the duals are finite circular split systems. Hence squaregraphs are at the crosspoint of two dualities, an algebraic and a geometric one, and thus lend themselves to several combinatorial interpretations and structural characterizations. With these and the 5-colorability theorem for circle graphs at hand, we prove that every squaregraph can be isometrically embedded into the Cartesian product of five trees. This embedding result can also be extended to the infinite case without reference to an embedding in the plane and without any cardinality restriction when formulated for median graphs free of cubes and further finite obstructions. Further, we exhibit a class of squaregraphs that can be embedded into the product of three trees and we characterize those squaregraphs that are embeddable into the product of just two trees. Finally, finite squaregraphs enjoy a number of algorithmic features that do not extend to arbitrary median graphs. For instance, we show that median-generating sets of finite squaregraphs can be computed in polynomial time, whereas, not unexpectedly, the corresponding problem for median graphs turns out to be NP-hard.Comment: 46 pages, 14 figure
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