1,721,018 research outputs found
A quadratically convergent Newton method for the nearest correlation matrix problem
No full textThe nearest correlation matrix problem is to find a correlation matrix which is closest to a given symmetric matrix in the Frobenius norm. The well-studied dual approach is to reformulate this problem as an unconstrained continuously differentiable convex optimization problem. Gradient methods and quasi-Newton methods such as BFGS have been used directly to obtain globally convergent methods. Since the objective function in the dual approach is not twice continuously differentiable, these methods converge at best linearly. In this paper, we investigate a Newton-type method for the nearest correlation matrix problem. Based on recent developments on strongly semismooth matrix valued functions, we prove the quadratic convergence of the proposed Newton method. Numerical experiments confirm the fast convergence and the high efficiency of the method
A Benders decomposition-based framework for solving quay crane scheduling problems
Full text linkIn this paper, we study the Quay Crane Scheduling Problem (QCSP) in container terminals. We describe a new mathematical formulation for the QCSP and by addressing the structure of workload assignments we develop an easier way to handle non-crossing constraints. The proposed mathematical formulation is used in an exact solution framework based on logic-based Benders decomposition. The proposed approach decomposes the problem into a workload-assignment master problem and operation-sequence slave subproblems. Logic-based cuts are proposed to ensure the convergence of the approach. Computational results show the effectiveness of the proposed solution approach
An exact algorithm for the unidirectional quay crane scheduling problem with vessel stability
No full textThis paper addresses the quay crane scheduling problem (QCSP) with vessel stability constraints. Vessel stability is essential to improve quay crane operations in container terminals, but it significantly com- plicates the basic QCSP and the corresponding solutions methods. We describe a novel mathematical formulation for the unidirectional QCSP with vessel stability, and we propose an exact algorithm based on logic-based Benders decomposition to solve the problem efficiently. The problem is decomposed into two subproblems, e.g., a task-assignment master problem without vessel stability constraints, and a time- allocation problem, aimed at determining the operation time of each task under the premise of the vessel stability requirements. The proposed algorithm is tested on benchmark instances derived from the litera- ture, and the effectiveness of the proposed model and solution approach is demonstrated
An augmented Lagrangian dual approach for the H-weighted nearest correlation matrix problem
No full textHigham (2002, IMA J. Numer. Anal., 22, 329–343) considered two types of nearest correlation matrix problems, namely the W-weighted case and the H-weighted case. While the W-weighted case has since been well studied to make several Lagrangian dual-based efficient numerical methods available, the H-weighted case remains numerically challenging. The difficulty of extending those methods from the W-weighted case to the H-weighted case lies in the fact that an analytic formula for the metric projection onto the positive semidefinite cone under the H-weight, unlike the case under the W-weight, is not available. In this paper we introduce an augmented Lagrangian dual-based approach that avoids the explicit computation of the metric projection under the H-weight. This method solves a sequence of unconstrained convex optimization problems, each of which can be efficiently solved by an inexact semismooth Newton method combined with the conjugate gradient method. Numerical experiments demonstrate that the augmented Lagrangian dual approach is not only fast but also robust
Spillover Effects in Task-Segment Switching: A Study of Translation Subtasks as Behavioral Categories Within the Task Segment Framework
No full textThe Task Segment Framework (TSF) is a systematic approach to the description and analysis of whole translation processes as keylogged that portrays translating as a metacognitively controlled activity steered by the translator. The TSF suggests that adding new text, changing existing copy, and online searching qualify as subtasks with psychological reality in that they are behavioral bundles with their own set of rules and palette of behaviors. As experience is accumulated, translators will tend to devote task segments to such single sub tasks to be more efficient, to avoid unnecessary higher mental loads derived from maintaining more than one set and palette active at once.
Using a wide variety of informants and texts, this research project sought to determine whether there are forward task-switching (spillover) effects, which would be a proof of such psychological reality. Three indicators were used, (1) the length of the previous pause chunking the task flow into task segments; and (2) the interkeystroke intervals (IKIs) and (3) the dwell time of the five first keypresses. The results of all three indicators attest for task switching effects and hence suggest that the translation subtasks in the TSF have psychological reality. Additional results point to IKI and dwell time rebound values that might be related to expertise but also with the smooth transition between chained typing motor programs
Introduction: One More Step Forward—Cognitive Translation Studies at the Start of a New Decade
No full textWe are witnessing exciting advances in cognitive translation studies (CTS), which has become an established area within translation studies. CTS boasts today an increasing number of researchers, diversified approaches to cognition and an expanded list of research topics. CTS-themed international conference series are contributing to the constant advances in this area in the new decade. Hence the title of this volume. In the first part of this introduction, we present a short history of the development of this area that, in a way, frames the introductions to each chapter in its second part by offering a wider perspective. Based on the “invisible college” thesis on the growth of scientific knowledge, our historical sketch is structured around CTS's emergence, early development, reckoning, rapid rise, and gradual diversification. As this book gets out of press, we emerge from a Covid-ridden year, and our CTS scientific community has paradoxically become more and better interconnected worldwide
Solving Karush-Kuhn-Tucker systems via the trust region and the conjugate gradient methods
No full textA popular approach to solving the Karush-Kuhn-Tucker (KKT) system, mainly arising from the variational inequality problem, is to reformulate it as a constrained minimization problem with simple bounds. In this paper, we propose a trust region method for solving the reformulation problem with the trust region subproblems being solved by the truncated conjugate gradient (CG) method, which is cost effective. Other advantages of the proposed method over existing ones include the fact that a good approximated solution to the trust region subproblem can be found by the truncated CG method and is judged in a simple way; also, the working matrix in each iteration is H, instead of the condensed H TH , where H is a matrix element of the generalized Jacobian of the function used in the reformulation. As a matter of fact, the matrix used is of reduced dimension. We pay extra attention to ensure the success of the truncated CG method as well as the feasibility of the iterates with respect to the simple constraints. Another feature of the proposed method is that we allow the merit function value to be increased at some iterations to speed up the convergence. Global and superlinear/quadratic convergence is shown under standard assumptions. Numerical results are reported on a subset of problems from the MCPLIB collection [S. P. Dirkse and M. C. Ferris, Optim. Methods Softw., 5 (1995), pp. 319-345]
<General Article> The Effect of Localization of Foreign Subsidiaries’ Top on Performance: The Moderator Role of Expatriates
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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
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