7 citations · 14 across the 8 of their papers we have counts for
8 papers
Hierarchically constrained blackbox optimization
Stéphane Alarie, Charles Audet, Paulin Jacquot +1
In blackbox optimization, evaluation of the objective and constraint functions is time consuming. In some situations, constraint values may be evaluated independently or sequential…
The equilateral small octagon of maximal width
Christian Bingane, Charles Audet
A small polygon is a polygon of unit diameter. The maximal width of an equilateral small polygon with vertices is not known when . This paper solves the first open…
Quantifying uncertainty with ensembles of surrogates for blackbox optimization
Charles Audet, Sébastien Le Digabel, Renaud Saltet
This work is in the context of blackbox optimization where the functions defining the problem are expensive to evaluate and where no derivatives are available. A tried and tested t…
Tight bounds on the maximal perimeter of convex equilateral small polygons
Christian Bingane, Charles Audet
A small polygon is a polygon that has diameter one. The maximal perimeter of a convex equilateral small polygon with sides is not known when . In this paper, we co…
Combining Cross Entropy and MADS methods for inequality constrained global optimization
Charles Audet, Romain Couderc, Jean Bigeon
This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS) algorithm with the Cross-Entropy (CE) method for non smooth constrained optimization. The CE method is u…
Optimization of noisy blackboxes with adaptive precision
Stéphane Alarie, Charles Audet, Pierre-Yves Bouchet +1
In derivative-free and blackbox optimization, the objective function is often evaluated through the execution of a computer program seen as a blackbox. It can be noisy, in the sens…
StoMADS: Stochastic blackbox optimization using probabilistic estimates
Charles Audet, Kwassi Joseph Dzahini, Michael Kokkolaras +1
This work introduces StoMADS, a stochastic variant of the mesh adaptive direct-search (MADS) algorithm originally developed for deterministic blackbox optimization. StoMADS conside…
Algorithmic construction of the subdifferential from directional derivatives
Charles Audet, Warren Hare
The subdifferential of a function is a generalization for nonsmooth functions of the concept of gradient. It is frequently used in variational analysis, particularly in the context…