activity
20122020
most citedAccelerating the DC algorithm for smooth functions

82 citations · 312 across the 12 of their papers we have counts for

collaborators

13 papers

math.OC2020

Strengthened Splitting Methods for Computing Resolvents

Francisco J. Aragón Artacho, Rubén Campoy, Matthew K. Tam

In this work, we develop a systematic framework for computing the resolvent of the sum of two or more monotone operators which only activates each operator in the sum individually.…

math.OC2019

The Douglas-Rachford Algorithm for Convex and Nonconvex Feasibility Problems

Francisco J. Aragón Artacho, Rubén Campoy, Matthew K. Tam

The Douglas-Rachford method, a projection algorithm designed to solve continuous optimization problems, forms the basis of a useful heuristic for solving combinatorial optimization…

math.OC2018★ 13 cited

Computing the resolvent of the sum of maximally monotone operators with the averaged alternating modified reflections algorithm

F. J. Aragón Artacho, R. Campoy

The averaged alternating modified reflections algorithm is a projection method for finding the closest point in the intersection of closed convex sets to a given point in a Hilbert…

math.OC2018

The Cyclic Douglas-Rachford Algorithm with r-sets-Douglas-Rachford Operators

Francisco J. Aragón Artacho, Yair Censor, Aviv Gibali

The Douglas-Rachford (DR) algorithm is an iterative procedure that uses sequential reflections onto convex sets and which has become popular for convex feasibility problems. In thi…

math.OC2017★ 7 cited

Optimal rates of linear convergence of the averaged alternating modified reflections method for two subspaces

Francisco J. Aragón Artacho, Rubén Campoy

The averaged alternating modified reflections (AAMR) method is a projection algorithm for finding the closest point in the intersection of convex sets to any arbitrary point in a H…

math.CO2017★ 11 cited

A feasibility approach for constructing combinatorial designs of circulant type

Francisco J. Aragón Artacho, Rubén Campoy, Ilias Kotsireas +1

In this work, we propose an optimization approach for constructing various classes of circulant combinatorial designs that can be defined in terms of autocorrelations. The problem…

math.OC2016

Solving graph coloring problems with the Douglas-Rachford algorithm

Francisco J. Aragón Artacho, Rubén Campoy

We present the Douglas-Rachford algorithm as a successful heuristic for solving graph coloring problems. Given a set of colors, these type of problems consist in assigning a color…

math.OC2016★ 23 cited

A new projection method for finding the closest point in the intersection of convex sets

Francisco J. Aragón Artacho, Rubén Campoy

In this paper we present a new iterative projection method for finding the closest point in the intersection of convex sets to any arbitrary point in a Hilbert space. This method,…

math.OC2015★ 82 cited

Accelerating the DC algorithm for smooth functions

Francisco J. Aragón Artacho, Ronan M. T. Fleming, Phan T. Vuong

We introduce two new algorithms to minimise smooth difference of convex (DC) functions that accelerate the convergence of the classical DC algorithm (DCA). We prove that the point…

math.OC2015★ 31 cited

Global Behavior of the Douglas-Rachford Method for a Nonconvex Feasibility Problem

Francisco J. Aragón Artacho, Jonathan M. Borwein, Matthew K. Tam

In recent times the Douglas-Rachford algorithm has been observed empirically to solve a variety of nonconvex feasibility problems including those of a combinatorial nature. For man…

math.OC2013★ 80 cited

Recent Results on Douglas-Rachford Methods for Combinatorial Optimization Problems

Francisco J. Aragón Artacho, Jonathan M. Borwein, Matthew K. Tam

We discuss recent positive experiences applying convex feasibility algorithms of Douglas--Rachford type to highly combinatorial and far from convex problems.

math.FA2013

Applications of Convex Analysis within Mathematics

Francisco J. Aragón Artacho, Jonathan M. Borwein, Victoria Martín-Márquez +1

In this paper, we study convex analysis and its theoretical applications. We first apply important tools of convex analysis to Optimization and to Analysis. We then show various de…

math.OC2012★ 65 cited

Global convergence of a non-convex Douglas-Rachford iteration

Francisco J. Aragón Artacho, Jonathan M. Borwein

We establish a region of convergence for the proto-typical non-convex Douglas-Rachford iteration which finds a point on the intersection of a line and a circle. Previous work on th…