Difference of Convex functions (DC) Programming and DC Algorithm (DCA) constitute the
backbone of Nonconvex Programming and Global Optimization. The paper is devoted to the …

The year 2015 marks the 30th birthday of DC (Difference of Convex functions) programming
and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and …

We investigate the convex–concave procedure, a local heuristic that utilizes the tools of
convex optimization to find local optima of difference of convex (DC) programming problems …

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 …

Optimization has been expanding in all directions at an astonishing rate during the last few
decades. New algorithmic and theoretical techniques have been developed, the diffusion …

The DC programming and its DC algorithm (DCA) address the problem of minimizing a
function f= g− h (with g, h being lower semicontinuous proper convex functions on R n) on …

This book is the first easy-to-read text on nonsmooth optimization (NSO, not necessarily
differentiable optimization). Solving these kinds of problems plays a critical role in many …

Sparse optimization refers to an optimization problem involving the zero-norm in objective or
constraints. In this paper, nonconvex approximation approaches for sparse optimization …

In the present paper, we are concerned with conditions ensuring the exact penalty for
nonconvex programming. Firstly, we consider problems with concave objective and …

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 …