Charles Audet

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The mesh adaptive direct search (MADS) algorithm is designed for blackbox optimization problems for which the functions defining the objective and the constr...

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We investigate surrogate-assisted strategies for global derivative-free optimization using the mesh adaptive direct search MADS blackbox optimization algorit...

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Despite the lack of theoretical and practical convergence support, the Nelder-Mead (NM) algorithm is widely used to solve unconstrained optimization proble...

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The calibration of hydrological models is here formulated as a Blackbox optimization problem where the only information available to the optimization algorit...

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The Runge-Kutta class of iterative methods is designed to approximate solutions of a system of ordinary differential equations (ODE). The second-order cla...

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Locally weighted regression combines the advantages of polynomial regression and kernel smoothing. We present three ideas for appropriate and effective use...

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The Mesh Adaptive Direct Search algorithm (MADS) is an iterative method for constrained blackbox optimization problems. One of the optional MADS features i...

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Blackbox optimization problems are often contaminated with numerical noise, and direct search methods such as the Mesh Adaptive Direct Search (MADS) algorit...

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The authors investigate the complexity needed in the structure of the scenario trees to maximize energy production in a rolling-horizon framework. Three comp...

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We present a new derivative-free trust-region (DFTR) algorithm to solve general nonlinear constrained problems with the use of an augmented Lagrangian m...

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We study derivative-free constrained optimization problems and propose a trust-region method that builds linear or quadratic models around the best feasible ...

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This paper presents an optimization method to solve the short-term unit commitment and loading problem with uncertain inflows. A scenario tree is built base...

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The subdifferential of a function is a generalization for nonsmooth functions of the concept of gradient. It is frequently used in variational analysis, part...

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The paper shows that among all equilateral polygons with a given number of sides and the same diameter, the regular polygon has the maximal area.

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This document describes the NOMAD software, a C++ implementation of the Mesh Adaptive Direct Search (MADS) algorithm designed for constrained optimization of...

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In prior works, this group demonstrated the feasibility of valid adaptive sequential designs for crossover bioequivalence studies. In this paper, we extend t...

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We study the function returning the sum of the k components of largest magnitude of a vector. We show that if a nonnegative vector x is such that its Eu...

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The Mesh Adaptive Direct Search (MADS) algorithm is designed for blackbox optimization problems subject to general inequality constraints. Currently, MADS do...

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This paper presents a new method for solving the short-term unit commitment and loading problem of a hydropower system. Dynamic programming is used to comput...

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Blackbox optimization deals with situations in which the objective function and constraints are typically computed by launching a time-consuming computer ...

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