In this paper, we extend a class of globally convergent evolution strategies to handle general constrained optimization problems. The proposed framework handles quantifiable relaxable constraints using a merit function approach combined with a specific restoration procedure. The unrelaxable constraints, when present, can be treated either by using ...
A port-Hamiltonian formulation for general linear coupled thermoelasticity and for the thermoelastic bending of thin structures is presented. The construction exploits the intrinsic modularity of port-Hamiltonian systems to obtain a formulation of linear thermoelasticity as an interconnection of the elastodynamics and heat equations. The derived mo...
Lors du développement de système critiques, comme par exemple un autopilote de drone, il est essentiel de s’assurer que le programme est sûr, en utilisant par exemple des méthodes formelles. Pour faciliter la vérification, on se restreint généralement à une abstraction du système ou un sous-ensemble. Cet article présente la vérification d’une bibli...
This paper presents the idea of multiscale parametrization for tropospheric refractivity inversion using gradient-based optimization method. Our motivation is to improve the accuracy of inversion without the use of apriori information. We retrieve the details of the refractivity distribution progressively from large to smaller scales using hierarch...
Recent applications in machine learning have renewed the interest of the community in min-max optimization problems. While gradient-based optimization methods are widely used to solve such problems, there are however many scenarios where these techniques are not well-suited, or even not applicable when the gradient is not accessible. We investigate...
Les changements climatiques entraînent régulièrement des phénomènes menaçant directement l'environnement et l'humanité. Dans ce contexte, la météorologie joue de plus en plus un rôle important dans la compréhension et la prévision de ces phénomènes. Le problème de fiabilisation des observations est essentiel pour le raisonnement numérique et la qua...
Bayesian optimization methods have been successfully applied to black box optimization problems that are expensive to evaluate. In this paper, we adapt the so-called super efficient global optimization algorithm to solve more accurately mixed constrained problems. The proposed approach handles constraints by means of upper trust bound, the latter e...
This paper investigates the time-local discretization, using Gaussian quadrature, of a class of diffusive operators that includes fractional operators, for application in fractional differential equations and related eigenvalue problems. A discretization based on the Gauss–Legendre quadrature rule is analyzed both theoretically and numerically. Num...
L'objectif de cet article est de définir un nouvel espace géométrique qui étend la notion de vecteur à des objets géométriques que nous nommerons secteur (portion de surface sous forme de parallélogramme). Nous en extrairons 3 propositions de structures algébriques qui étendent les notions de groupe, corps et espace vectoriel. Ces structures seront...
The Levenberg–Marquardt algorithm is one of the most popular algorithms for finding the solution of nonlinear least squares problems. Across different modified variations of the basic procedure, the algorithm enjoys global convergence, a competitive worst-case iteration complexity rate, and a guaranteed rate of local convergence for both zero and n...
