This survey examines the state of the art of a variety of problems related to pseudo-Boolean
optimization, ie to the optimization of set functions represented by closed algebraic …

Written by prominent experts in the field, this monograph provides the first comprehensive,
unified presentation of the structural, algorithmic and applied aspects of the theory of …

This survey covers the state of the art of techniques for solving general-purpose constrained
global optimization problems and continuous constraint satisfaction problems, with …

The first systematic overviews on global optimization appeared in 1975–1978 thanks to two
fundamental volumes titled Towards Global Optimization (Dixon & Szegö, 1975, 1978). At …

This book is an expository introduction to the methodology of sensitivity analysis of model
output. It is primarily intended for investigators, students and researchers that are familiar …

Convex envelopes of multilinear functions on a unit hypercube arepolyhedral. This well-
known fact makes the convex envelopeapproximation very useful in the linearization of non …

Tree ensemble models such as random forests and boosted trees are among the most
widely used and practically successful predictive models in applied machine learning and …

We define a convex extension of a lower semi-continuous function to be a convex function
that is identical to the given function over a pre-specified subset of its domain. Convex …

Convex underestimators of nonconvex functions, frequently used in deterministic global
optimization algorithms, strongly influence their rate of convergence and computational …

In this paper, we derive explicit characterizations of convex and concave envelopes of
several nonlinear functions over various subsets of a hyper-rectangle. These envelopes are …