3 citations · 6 across the 10 of their papers we have counts for
10 papers
Adaptive direct search algorithms with relaxable and quantifiable constraints
Charles Audet, Théo Denorme, Youssef Diouane +2
This work introduces ADS-PB, an extension of the Adaptive Direct Search (ADS) framework for solving constrained blackbox optimization problems. With ADS, iterates progress without…
Benchmarking Bilevel Derivative-Free Optimization Algorithms
Charles Audet, Valentin Dijon, Youssef Diouane
Bilevel optimization involves an upper-level and a lower-level decision maker. The lower-level optimization problem is nested within the constraints of the upper-level one. A point…
Surrogate-based categorical neighborhoods for mixed-variable blackbox optimization
Charles Audet, Youssef Diouane, Edward Hallé-Hannan +2
In simulation-based engineering, design choices are often obtained following the optimization of complex blackbox models. These models frequently involve mixed-variable domains wit…
A penalty-interior point method combined with MADS for equality and inequality constrained optimization
Charles Audet, Andrea Brilli, Youssef Diouane +3
This work introduces MADS-PIP, an efficient framework that integrates a penalty-interior point strategy into the mesh adaptive direct search (MADS) algorithm for solving nonsmooth…
Multi-fidelity constraints in blackbox optimization
Stéphane Alarie, Charles Audet, Miguel Diago +2
This work studies constrained blackbox optimization problems that cannot be solved in reasonable time due to prohibitive computational costs. This challenge is especially prevalent…
Adaptive direct search algorithms for constrained optimization
Charles Audet, Théo Denorme, Youssef Diouane +2
Two families of directional direct search methods have emerged in derivative-free and blackbox optimization (DFO and BBO), each based on distinct principles: Mesh Adaptive Direct S…
CatMADS: Mesh Adaptive Direct Search for constrained blackbox optimization with categorical variables
Charles Audet, Youssef Diouane, Edward Hallé-Hannan +2
Solving optimization problems in which functions are blackboxes and variables involve different types poses significant theoretical and algorithmic challenges. Nevertheless, such s…
solar: A solar thermal power plant simulator for blackbox optimization benchmarking
Nicolau Andrés-Thió, Charles Audet, Miguel Diago +5
This work introduces solar, a collection of ten optimization problem instances for benchmarking blackbox optimization solvers. The instances present different design aspects of a c…
A distance for mixed-variable and hierarchical domains with meta variables
Edward Hallé-Hannan, Charles Audet, Youssef Diouane +2
Heterogeneous datasets emerge in various machine learning and optimization applications that feature different input sources, types or formats. Most models or methods do not native…
Fidelity and interruption control for expensive constrained multi-fidelity blackbox optimization
Stéphane Alarie, Charles Audet, Miguel Diago +2
This work introduces a novel blackbox optimization algorithm for computationally expensive constrained multi-fidelity problems. When applying a direct search method to such problem…