The time-stamped database provided by Google traces the code contributions to Chrome browser on the period from September 2008 to January 2014. It describes ...

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

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 ...

We introduce an iterative method named GPMR for solving 2X2 block unsymmetric linear systems. GPMR is based on a new process that reduces simultaneously...

This paper presents an efficient method for extracting the second-order sensitivities from a system of implicit nonlinear equations. We design a custom aut...

For a simple connected graph \(G\), let \(D(G), ~Tr(G)\), \(D^{L}(G)=Tr(G)-D(G)\), and \(D^{Q}(G)=Tr(G)+D(G)\) be the distance matrix, the diagonal m...

In this paper, we consider both first- and second-order techniques to address continuous optimization problems arising in machine learning. In the first-orde...

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...

The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that sh...

The Quadratic Knapsack Problem (QKP) is a well-known combinatorial optimization problem which amounts to maximizing a quadratic function of binary variables,...

NOMAD is software for optimizing blackbox problems. In continuous development since 2001, it constantly evolved with the integration of new algorithmic...

We introduce iterative methods named TriCG and TriMR for solving symmetric quasi-definite systems based on the orthogonal tridiagonalization process proposed...

Algorithm NCL is designed for general smooth optimization problems
    where first and second derivatives are available,
    including problems whose constrai...

We describe a Julia implementation of Mehrotra's predictor-corrector method for convex quadratic optimization that is entirely open source and generic in tha...

We consider computationally expensive blackbox optimization problems and present a method that employs surrogate models and concurrent computing at the searc...

This work introduces the StoMADS-PB algorithm for constrained stochastic blackbox optimization, which is an extension of the mesh adaptive direct-search (MAD...

This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS) algorithm with the Cross-Entropy (CE) method for non smooth constrained optimizat...

The Ninth Montreal IPSW took place on August 19-23, 2019, and was jointly organized by the CRM and IVADO (Institute for Data Valorization). The workshop welc...

We propose a new stochastic variance-reduced damped L-BFGS algorithm, where we leverage estimates of bounds on the largest and smallest eigenvalues of the He...

This work reviews blackbox optimization applications over the last twenty years, addressed using direct search optimization methods. Emphasis is placed on...