Charles Audet

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134 results — page 1 of 7

Solving optimization problems in which functions are blackboxes and variables involve different types poses significant theoretical and algorithmic challeng...

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Benchmarking new optimization methods on test problems is essential for assessing their performance and tuning their parameters. Yet, few problems are avail...

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Benchmarking is essential for assessing the effectiveness of optimization algorithms. This is especially true in derivative-free optimization, where target ...

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Researchers around the globe attend the International Symposium on Mathematical Programming (ISMP) to share their latest results in mathematics, algorithms, ...

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Bistable mechanical systems exhibit two stable configurations where the elastic energy is locally minimized. To realize such systems, origami techniques ha...

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This work introduces a _partitioned optimization framework_ (POf) to ease the solving process for optimization problems for which fixing some variables to a...

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This paper introduces a new step to the Direct Search Method (DSM) to strengthen its convergence analysis. By design, this so-called covering step may e...

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This work introduces solar, a collection of ten optimization problem instances for benchmarking blackbox optimization solvers. The instances present differ...

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Heterogeneous datasets emerge in various machine learning or optimization applications that feature different data sources, various data types and complex re...

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The cosine measure was introduced in 2003 to quantify the richness of a finite positive spanning sets of directions in the context of derivative-free direc...

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This work introduces a novel multi-fidelity blackbox optimization algorithm designed to alleviate the resource-intensive task of evaluating infeasible points...

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This paper addresses risk averse constrained optimization problems where the objective and constraint functions can only be computed by a blackbox subject to...

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This work considers stochastic optimization problems in which the objective function values can only be computed by a blackbox corrupted by some random noise...

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This note provides a counterexample to a theorem announced in the last part of the paper Analysis of direct searches for discontinuous functions, Mathemati...

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A mathematical framework for modelling constrained mixed-variable optimization problems is presented in a blackbox optimization context. The framework intr...

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Engineering design is often faced with uncertainties, making it difficult to determine an optimal design. In an unconstrained context, this amounts to choose...

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In blackbox optimization, evaluation of the objective and constraint functions is time consuming. In some situations, constraint values may be evaluated in...

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A piecewise constant Mayer cost function is used to model optimal control problems in which the state space is partitioned into several regions, each having ...

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A small polygon is a polygon of unit diameter. The maximal width of an equilateral small polygon with n=2s vertices is not known when s3. T...

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This work is in the context of blackbox optimization where the functions defining the problem are expensive to evaluate and where no derivatives are availabl...

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