Recent advances in DC programming and DCA
T Pham Dinh, HA Le Thi - Transactions on computational intelligence XIII, 2014 - Springer
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 …
backbone of Nonconvex Programming and Global Optimization. The paper is devoted to the …
DC programming and DCA: thirty years of developments
HA Le Thi, T Pham Dinh - Mathematical Programming, 2018 - Springer
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 …
and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and …
Variations and extension of the convex–concave procedure
T Lipp, S Boyd - Optimization and Engineering, 2016 - Springer
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 …
convex optimization to find local optima of difference of convex (DC) programming problems …
Euclidean distance geometry and applications
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 …
distance. This is useful in several applications where the input data consist of an incomplete …
[图书][B] Convex analysis and global optimization
H Tuy, T Hoang, T Hoang, V Mathématicien, T Hoang… - 1998 - Springer
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 …
decades. New algorithmic and theoretical techniques have been developed, the diffusion …
The DC (difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
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 …
function f= g− h (with g, h being lower semicontinuous proper convex functions on R n) on …
[图书][B] Introduction to Nonsmooth Optimization: theory, practice and software
A Bagirov, N Karmitsa, MM Mäkelä - 2014 - Springer
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 …
differentiable optimization). Solving these kinds of problems plays a critical role in many …
DC approximation approaches for sparse optimization
Sparse optimization refers to an optimization problem involving the zero-norm in objective or
constraints. In this paper, nonconvex approximation approaches for sparse optimization …
constraints. In this paper, nonconvex approximation approaches for sparse optimization …
Exact penalty and error bounds in DC programming
In the present paper, we are concerned with conditions ensuring the exact penalty for
nonconvex programming. Firstly, we consider problems with concave objective and …
nonconvex programming. Firstly, we consider problems with concave objective and …
The discretizable molecular distance geometry problem
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 …
Distance Geometry Problem (MDGP) consists in finding an embedding x: V→ ℝ 3 such …