Université libre de Bruxelles

About: Université libre de Bruxelles is a education organization based out in Brussels, Belgium. It is known for research contribution in the topics: Population & Breast cancer. The organization has 24974 authors who have published 56969 publications receiving 2084303 citations. The organization is also known as: ULB.

The Generalized Dynamic-Factor Model: Identification and Estimation

Abstract: This paper proposes a factor model with infinite dynamics and nonorthogonal idiosyncratic components. The model, which we call the generalized dynamic-factor model, is novel to the literature and generalizes the static approximate factor model of Chamberlain and Rothschild (1983), as well as the exact factor model a la Sargent and Sims (1977). We provide identification conditions, propose an estimator of the common components, prove convergence as both time and cross-sectional size go to infinity at appropriate rates, and present simulation results. We use our model to construct a coincident index for the European Union. Such index is defined as the common component of real GDP within a model including several macroeconomic variables for each European country.

Self-consistent mean-field models for nuclear structure

Abstract: The authors review the present status of self-consistent mean-field (SCMF) models for describing nuclear structure and low-energy dynamics. These models are presented as effective energy-density functionals. The three most widely used variants of SCMF's based on a Skyrme energy functional, a Gogny force, and a relativistic mean-field Lagrangian are considered side by side. The crucial role of the treatment of pairing correlations is pointed out in each case. The authors discuss other related nuclear structure models and present several extensions beyond the mean-field model which are currently used. Phenomenological adjustment of the model parameters is discussed in detail. The performance quality of the SCMF model is demonstrated for a broad range of typical applications.

Ant colony optimization: a new meta-heuristic

Abstract: Recently, a number of algorithms inspired by the foraging behavior of ant colonies have been applied to the solution of difficult discrete optimization problems. We put these algorithms in a common framework by defining the Ant Colony Optimization (ACO) meta-heuristic. A couple of paradigmatic examples of applications of these novel meta-heuristic are given, as well as a brief overview of existing applications.

The ant colony optimization meta-heuristic

Abstract: This chapter contains sections titled: Combinatorial Optimization, The ACO Metaheuristic, How Do I Apply ACO?, Other Metaheuristics, Bibliographical Remarks, Things to Remember, Thought and Computer Exercises