Introduced in 1993, the DIRECT global optimization algorithm provided a fresh approach to
minimizing a black-box function subject to lower and upper bounds on the variables. In …

We investigate the potential of applying a state-of-the-art, local derivative-free solver, Py-
BOBYQA to global optimization problems. In particular, we demonstrate the potential of a …

This paper introduces an innovative extension of the DIRECT algorithm specifically
designed to solve global optimization problems that involve Lipschitz continuous functions …

This work presents recent advances within the AlgoRithms for Global Optimization of
coNstrAined grey-box compUTational problems (ARGONAUT) framework, developed for …

In this work, we introduce DIRECTGO, a new MATLAB toolbox for derivative-free global
optimization. DIRECTGO collects various deterministic derivative-free DIRECT-type …

This paper presents a sequential model based optimization framework for optimizing a black-
box, multi-extremal and expensive objective function, which is also partially defined, that is it …

This article considers a box-constrained global optimization problem for Lipschitz-
continuous functions with an unknown Lipschitz constant. Motivated by the famous DIRECT …

The paper is concerned with black-box nonlinear constrained multi-objective optimization
problems. Our interest is the definition of a multi-objective deterministic partition-based …

Applied optimization problems often include constraints. Although the well-known derivative-
free global-search DIRECT algorithm performs well solving box-constrained global …

In this paper, we consider the solution of global optimization problems involving hidden
constraints. We present a novel deterministic derivative-free global optimization algorithm …