1,720,998 research outputs found
Cabin crew rostering at KLM : optimization of reserves
No full textIn this paper, we will discuss the issue of rostering jobs of cabin crew attendants at KLM.
Generated schedules get easily disrupted by events such as illness of an employee. Obviously, reserve people have to be kept ‘on duty’ to resolve such disruptions. A lot of reserve crew requires more employees, but too few results in so-called secondary disruptions, which are particularly inconvenient for both the crew members and the planners. In this research we will discuss several modifications of the reserve scheduling policy that have a potential to reduce the number of secondary disruptions, and therefore to improve the performance of the scheduling process
GPU Acceleration of Graph Matching, Clustering, and Partitioning
No full textWe consider sequential algorithms for hypergraph partitioning and GPU (i.e., fine-grained shared-memory parallel) algorithms for graph partitioning and clustering. Our investigation into sequential hypergraph partitioning is concerned with the efficient construction of high-quality matchings for hypergraph coarsening and optimisation with respect to general hypergraph partitioning quality metrics. We introduce the l*(l-1)-metric which exactly measures the communication volume for a finite element computation, and show how to use an ordinary hypergraph bipartitioner to greedily optimise a partitioning with respect to a general quality metric. Graph partitioning and clustering on the GPU is achieved by implementing all parts of the multi-level paradigm (i.e., matching, coarsening, and refinement) on the GPU. We first develop GPU algorithms for matching and coarsening. These are then used as building blocks for a greedy agglomerative modularity clustering heuristic, with which we participated in the 10th DIMACS partitioning and clustering challenge. By combining the parallel matching and coarsening algorithms with a parallel partitioning refinement method and implementing these algorithms using general sparse matrix-vector multiplication operations, we are able to perform graph partitioning entirely on the GPU. The GPU partitioning algorithm is compared both in terms of quality and speed to the sequential METIS graph partitioner and is faster for graphs with a million or more vertices, while offering similar quality. The highest achieved speedup over METIS is 6.2, for which a graph with 24 million vertices and 29 million edges is partitioned into two parts in 3.7 seconds on the GPU (an NVIDIA Tesla C2075) with an edge cut of 329. This shows that the GPU can effectively be used for the multi-level analysis of large graphs
Fast sparse matrix-vector multiplication by partitioning and reordering
No full textThe thesis introduces a cache-oblivious method for the sparse matrix-vector (SpMV) multiplication, which is an important computational kernel in many applications. The method works by permuting rows and columns of the input matrix so that the resulting reordered matrix induces cache-friendly behaviour during the SpMV multiply. This matrix reordering is obtained by using a recursive sparse matrix partitioning scheme, based on hypergraph partitioning, and is deeply linked to earlier partitioning schemes for distributed parallel SpMV multiplication. Initially, the input sparse matrix is modelled as a one-dimensional hypergraph. Extending this to a standard two-dimensional model while still allowing the reordering method to perform only row and column permutations, requires a generalisation of the standard Compressed Row Storage data structure to a block-based data structure. It is shown which recursive block ordering is asymptotically optimal. Furthermore, using the techniques developed for the 2D method, another cache-oblivious method based on the Hilbert curve is developed. All these methods are cache-oblivious in that the reordering algorithm does not depend on cache parameters of specific target architectures. Experiments performed on three different architectures show that the 1D method can improve SpMV multiplication performance of unstructured sparse matrices up to a factor two. The adapted Hilbert scheme is somewhat less effective, whereas the two-dimensional method typically performs better; there, the largest gain is over a factor of three. To further speed up the SpMV multiplication on multicore architectures, the performance of parallel SpMV multiplication is investigated using the Bulk Synchronous Parallel (BSP) model and the proof-of-concept MulticoreBSP library. This library is written in Java and explicitly targets shared-memory systems, and is furthermore applied to the problems of fast Fourier transformation as well as the dense LU decomposition. This parallel scheme is also applied in tandem with cache-oblivious reordering to obtain a full parallel cache-oblivious scheme. Plain parallelisation resulted in a maximum speedup of 3.5 for four threads, thus showing that the BSP model applies well to shared-memory multicore systems. Combined with reordering, superlinear speedups become possible: in one case a gain of a factor 2.8 was attained while using only two threads
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Numerical Methods for Nonlinear Elliptic Boundary Value Problems with Parameter Dependence
No full textThis thesis discusses numerical methods for nonlinear elliptic partial differential equations with parameter dependence such as the Gelfand-Bratu model and singularly perturbed convection-diffusion-reaction equations. In numerical investigations, more accurate and efficient nonstandard finite difference and multigrid methods are adopted to solve parameter dependent elliptic boundary-value problems. Aim and objectives of the research are given in chapter 1. Further, it describes the background of Gelfand-Bratu and singularly perturbed problems. In addition, an overview of nonstandard finite difference and multigrid methods is given followed by an outline of the thesis. In chapter 2, standard and nonstandard finite difference approximations are employed to find the numerical solutions of the one-dimensional truncated Bratu-Picard (BP) model. Numerical results show the existence of infinitely many solutions, which are calculated numerically (for a large, but finite, set of solutions). These new types of solutions are either periodic or semi-periodic. We observe that the nonstandard finite difference schemes provide more accurate and efficient results than standard finite difference schemes. In chapter 3, we propose a higher order non-uniform finite difference grid, to solve singularly perturbed boundary value problems with steep boundary-layers. Theoretical properties concerning the extremum values and the asymptotic value at the right boundary point are presented. Several examples are provided, which demonstrate the effectiveness of the proposed numerical strategy. We establish numerically, not only 4th-order but also a 6th-order of accuracy by considering only three-point central non-uniform finite differences. Numerical results illustrate that to achieve the 6th-order of accuracy, the proposed method needs approximately a factor of 5-10 fewer grid points than the uniform case. In chapter 4, we propose three numerical methods, viz, a finite-difference approximation and two multigrid (MG) approaches: Newton-MG and Full Approximation Storage (FAS). A comparison, in terms of convergence, accuracy and efficiency among the three numerical methods demonstrate improvement for the whole parameter range λ ∈ (0, λc]. Further, we investigate the bifurcation behaviour of solutions and find new multiplicity of solutions in the case of a cubic approximation of the nonlinear exponential term. We demonstrate that the convergence of all solutions namely, unique, lower, upper, periodic and semi-periodic is obtained for small values of the parameter λ. Particularly, FAS-MG is found to be more efficient than the other two methods. In chapter 5, we present a numerical study of the Gelfand-Bratu model for higher dimensions. For three dimensions, we adopt an accurate and efficient nonlinear multigrid approach, namely, FAS-MG extended with a Krylov method as a smoother. New types of solutions are obtained or specific values of the bifurcation parameter. Further, the numerical bifurcation curve of the Gelfand-Bratu problem in three dimensions shows the existence of two new turning points. Numerical results confirm the convergence of all types of solutions and demonstrate the effectiveness of the proposed numerical strategy. For even higher dimensions, numerical experiments show the existence of several types of solutions. Bifurcation curves confirm the theoretical results of the higher-dimensional Gelfand-Bratu problem as presented in the literature
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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