60 research outputs found

    Peter\u27s Work: A Tribute to Professor Peter M. Cicchino

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    A Declarative Paradigm for Robust Cumulative Scheduling

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    International audienceThis paper investigates cumulative scheduling in uncertain environments, using constraint programming. We present a new declarative characterization of robustness, which preserves solution quality.We highlight the significance of our framework on a crane assignment problem with business constraints

    Spin randomization of light-induced desorbed Rb atoms

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    We present the first experimental observation of atomic spin randomization of Rb atoms released by light-induced atomic desorption (LIAD). A natural mixture of Rb atoms contained in paraffin and PDMS coated glass cells is irradiated by a free-running diode laser light tuned to the Rb D2 resonance line. The transmission spectrum of the Rb vapor is thus modified and shows a strong enhancement of the hyperfine optical pumping as the light intensity is increased and the laser-frequency scanning rate is decreased. The D2 line spectra are compared for two cases: without and with illumination of the walls of the cell by a UV lamp centered around the wavelength of 404 nm. A simple theoretical model based on the solution of the rate balance equations is introduced in order to analyze the experimental results

    The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees

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    Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma

    A Parallel, Backjumping Subgraph Isomorphism Algorithm Using Supplemental Graphs

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    This registry entry contains a reference to the code, data and experimental scripts needed to reproduce the subgraph isomorphism paper: Ciaran McCreesh and Patrick Prosser, "A Parallel, Backjumping Subgraph Isomorphism Algorithm using Supplemental Graphs". To appear at the 21st International Conference on Principles and Practice of Constraint Programming (CP 2015)

    Sequential and parallel solution-biased search for subgraph algorithms

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    Funding: This work was supported by the Engineering and Physical Sciences Research Council (grant numbers EP/P026842/1, EP/M508056/1, and EP/N007565).The current state of the art in subgraph isomorphism solving involves using degree as a value-ordering heuristic to direct backtracking search. Such a search makes a heavy commitment to the first branching choice, which is often incorrect. To mitigate this, we introduce and evaluate a new approach, which we call “solution-biased search”. By combining a slightly-random value-ordering heuristic, rapid restarts, and nogood recording, we design an algorithm which instead uses degree to direct the proportion of search effort spent in different subproblems. This increases performance by two orders of magnitude on satisfiable instances, whilst not affecting performance on unsatisfiable instances. This algorithm can also be parallelised in a very simple but effective way: across both satisfiable and unsatisfiable instances, we get a further speedup of over thirty from thirty-six cores, and over one hundred from ten distributed-memory hosts. Finally, we show that solution-biased search is also suitable for optimisation problems, by using it to improve two maximum common induced subgraph algorithms.Postprin

    Peter\u27s Work: A Tribute to Professor Peter M. Cicchino

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