Many industrial problems can be naturally formulated using mixed integer non-linear
programming (MINLP) models and can be solved by spatial Branch&Bound (sBB) techniques. We …

Euclidean distance geometry is the study of Euclidean geometry based on the concept of
distance. This is useful in several applications where the input data consist of an incomplete …

Most books about global optimization describe the theory of the algorithms, whereas a given
implementation’s quality never depends exclusively on the theoretical soundness of the …

What do clocks, wireless devices, atoms, and submarines have in common? They move: the
clocks move time forward (so to speak), wireless devices usually move on a plane (like an …

Accurate modelling of real-world problems often requires nonconvex terms to be introduced
in the model, either in the objective function or in the constraints. Nonconvex programming …

Data are often represented as graphs. Many common tasks in data science are based on
distances between entities. While some data science methodologies natively take graphs as …

Given a simple weighted undirected graph G=(V,E,d) with d:E→ℝ + , the Molecular Distance
Geometry Problem (MDGP) consists in finding an embedding x:V→ℝ 3 such that ‖x u −x v …

In this paper, we survey methods that are currently used in black‐box optimization, that is,
the kind of problems whose objective functions are very expensive to evaluate and no …

The Molecular Distance Geometry Problem consists in finding the positions in of the atoms
of a molecule, given some of the inter‐atomic distances. We show that under an additional …

If a mathematical program has many symmetric optima, solving it via Branch-and-Bound
techniques often yields search trees of disproportionate sizes; thus, finding and exploiting …