A Declarative Paradigm for Robust Cumulative Scheduling

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

Experimental Evaluation of Subgraph Isomorphism Solvers

International audienceSubgraph Isomorphism (SI) is an NP-complete problem which is at the heart of many structural pattern recognition tasks as it involves finding a copy of a pattern graph into a target graph. In the pattern recognition community, the most well-known SI solvers are VF2, VF3, and RI. SI is also widely studied in the constraint programming community, and many constraint-based SI solvers have been proposed since Ullman, such as LAD and Glasgow, for example. All these SI solvers can solve very quickly some large SI instances, that involve graphs with thousands of nodes. However, McCreesh et al. have recently shown how to randomly generate SI instances the hardness of which can be controlled and predicted, and they have built small instances which are computationally challenging for all solvers. They have also shown that some small instances, which are predicted to be easy and are easily solved by constraint-based solvers, appear to be challenging for VF2 and VF3. In this paper, we widen this study by considering a large test suite coming from eight benchmarks. We show that, as expected for an NP-complete problem, the solving time of an instance does not depend on its size, and that some small instances coming from real applications are not solved by any of the considered solvers. We also show that, if RI and VF3 can solve very quickly a large number of easy instances, for which Glasgow or LAD need more time, they fail at solving some other instances that are quickly solved by Glasgow or LAD, and they are clearly outperformed by Glasgow on hard instances. Finally, we show that we can easily combine solvers to take benefit of their complementarity

Revisiting the tree Constraint

International audienceThis paper revisits the tree constraint introduced in [2] which partitions the nodes of a n-nodes, m-arcs directed graph into a set of node-disjoint anti-arborescences for which only certain nodes can be tree roots. We introduce a new filtering algorithm that enforces generalized arc-consistency in O(n + m) time while the original filtering algorithm reaches O(nm) time. This result allows to tackle larger scale problems involving graph partitioning

Flexible graph matching and graph edit distance using answer set programming

The graph isomorphism, subgraph isomorphism, and graph edit distance problems are combinatorial problems with many applications. Heuristic exact and approximate algorithms for each of these problems have been developed for different kinds of graphs: directed, undirected, labeled, etc. However, additional work is often needed to adapt such algorithms to different classes of graphs, for example to accommodate both labels and property annotations on nodes and edges. In this paper, we propose an approach based on answer set programming. We show how each of these problems can be defined for a general class of property graphs with directed edges, and labels and key-value properties annotating both nodes and edges. We evaluate this approach on a variety of synthetic and realistic graphs, demonstrating that it is feasible as a rapid prototyping approach.Comment: To appear, PADL 202

Spin randomization of light-induced desorbed Rb atoms

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

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

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

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