Titlebook: LATIN 2014: Theoretical Informatics; 11th Latin American Alberto Pardo,Alfredo Viola Conference proceedings 2014 Springer-Verlag Berlin He

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Hierarchical Complexity of 2-Clique-Colouring Weakly Chordal Graphs and Perfect Graphs Having Cliquehe vertices with at most . colours such that no clique is monochromatic. Défossez proved that the 2-clique-colouring of perfect graphs is a .-complete problem [J. Graph Theory 62 (2009) 139–156]. We strengthen this result by showing that it is still .-complete for weakly chordal graphs. We then dete

Functional

The Computational Complexity of the Game of Set and Its Theoretical Applicationsi-round variations of this game from the computational complexity point of view and establish interesting connections with other classical computational problems..Specifically, we first show that a natural generalization of the problem of finding a single Set, parameterized by the size of the sought

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Independent and Hitting Sets of Rectangles Intersecting a Diagonal Lineroblem has attracted significant attention since the sixties, when Wegner conjectured that the corresponding duality gap, i.e., the maximum possible ratio between the maximum independent set and the minimum hitting set, is bounded by a universal constant. In this paper we improve upon recent results

Saline

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False-Name Manipulation in Weighted Voting Games Is Hard for Probabilistic Polynomial Timeand distributing her weight among these false identities. Analogously to this splitting problem, the beneficial merging problem asks whether a coalition of players can increase their power in a weighted voting game by merging their weights. Aziz et al. [1] analyze the problem of whether merging or s

印第安人

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Optimal Algorithms for Constrained 1-Center Problems Φ. We first study the case when Γ is a set of . points and Φ is either a set of points, a set of segments (lines) or a simple polygon. We propose several algorithms, the first solves the problem when Φ is a set of . segments (or . points) in expected Θ((. + .)log.) time, where . =  min {., .}. Surp

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