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

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

An augmented Lagrangian (AL) can convert a constrained optimization problem into a sequence of simpler (e.g., unconstrained) problems, which are then usual...

We consider the maximum \(k\)-cut problem that consists in partitioning the vertex set of a graph into \(k\) subsets such that the sum of the weights o...

This work describes the application of a direct search method to the optimization of problems of real industrial interest, namely three new material scien...

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

The types of constraints encountered in black-box and simulation-based optimization problems differ significantly from those treated in nonlinear programmin...

Various constrained problem formulations for the optimization of an electro-thermal wing anti-icing system in both running-wet and evaporative regimes are pr...

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

Constrained blackbox optimization is a difficult problem, with most approaches coming from the mathematical programming literature. The statistical literatur...

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

Typical challenges of simulation-based design optimization include unavailable gradients and unreliable approximations thereof, expensive function evaluation...

This work introduces the use of the treed Gaussian process (TGP) as a surrogate model within the mesh adaptive direct search (MADS) framework for constrain...

The Mesh Adaptive Direct Search (MADS) class of algorithms is designed for nonsmooth optimization, where the objective function and constraints are typical...

We present ACRE, an Automatic aspeCt cREator, to use aspect-oriented programming to test multi-platform software programs written in C++. ACRE allows devel...

We consider derivative-free optimization, and in particular black box optimization, where the functions to minimize and the functions representing the con...

Accurate measurements of snow water equivalent (SWE) is an important factor in managing water resources for hydroelectric power generation. SWE over a catchm...

During alloy and process design, it is often desired to identify regions of design or process variables for which certain calculated functions have optimal v...

The present paper describes the coupling of the Mesh Adaptive Direct Search (MADS) algorithm with the FactSage thermochemical software, which allows to calcu...

The paper proposes a framework for sensitivity analyses of blackbox constrained optimization problems for which Lagrange multipliers are not available. Two s...