26 research outputs found

    On the NP-Hardness of Approximating Ordering Constraint Satisfaction Problems

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    We show improved NP-hardness of approximating Ordering Constraint Satisfaction Problems (OCSPs). For the two most well-studied OCSPs, Maximum Acyclic Subgraph and Maximum Betweenness, we prove inapproximability of 14/15+ϵ14/15+\epsilon and 1/2+ϵ1/2+\epsilon. An OCSP is said to be approximation resistant if it is hard to approximate better than taking a uniformly random ordering. We prove that the Maximum Non-Betweenness Problem is approximation resistant and that there are width-mm approximation-resistant OCSPs accepting only a fraction 1/(m/2)!1 / (m/2)! of assignments. These results provide the first examples of approximation-resistant OCSPs subject only to P ≠\neq \NP

    On Solving the Maximum Betweenness Problem Using Genetic Algorithms

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    In this paper a genetic algorithm (GA) is applied on Maximum Betweennes Problem (MBP). The maximum of the objective function is obtained by finding a permutation which satisfies a maximal number of betweenness constraints. Every permutation considered is genetically coded with an integer representation. Standard operators are used in the GA. Instances in the experimental results are randomly generated. For smaller dimensions, optimal solutions of MBP are obtained by total enumeration. For those instances, the GA reached all optimal solutions except one. The GA also obtained results for larger instances of up to 50 elements and 1000 triples. The running time of execution and finding optimal results is quite short

    Variations on an ordering theme with constraints

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    We investigate the problem of nding a total order of a nite set that satis es various local ordering constraints. Depending on the admitted constraints, we provide an e cient algorithm or prove NP-completeness. We discuss several generalisations and systematically classify the problems4th IFIP International Conference on Theoretical Computer ScienceRed de Universidades con Carreras en Informática (RedUNCI

    Learning Lines with Ordinal Constraints

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    We study the problem of finding a mapping f from a set of points into the real line, under ordinal triple constraints. An ordinal constraint for a triple of points (u,v,w) asserts that |f(u)-f(v)| < |f(u)-f(w)|. We present an approximation algorithm for the dense case of this problem. Given an instance that admits a solution that satisfies (1-?)-fraction of all constraints, our algorithm computes a solution that satisfies (1-O(?^{1/8}))-fraction of all constraints, in time O(n?) + (1/?)^{O(1/?^{1/8})} n
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