Recent Results on Douglas-Rachford Methods for Combinatorial Optimization Problems
arXiv:1305.2657 · doi:10.1007/s10957-013-0488-0
Abstract
We discuss recent positive experiences applying convex feasibility algorithms of Douglas--Rachford type to highly combinatorial and far from convex problems.
References in corpus (3)
Cited by in corpus (24)
- Douglas-Rachford splitting for nonconvex optimization with application to nonconvex feasibility problems
- Convergence rate analysis for averaged fixed point iterations in the presence of Hölder regularity
- Circumcentering the Douglas--Rachford method
- Global Behavior of the Douglas-Rachford Method for a Nonconvex Feasibility Problem
- On the linear convergence of the circumcentered-reflection method
- A new projection method for finding the closest point in the intersection of convex sets
- The rate of linear convergence of the Douglas-Rachford algorithm for subspaces is the cosine of the Friedrichs angle
- On the finite convergence of the Douglas-Rachford algorithm for solving (not necessarily convex) feasibility problems in Euclidean spaces
- Dynamics of the Douglas-Rachford Method for Ellipses and p-Spheres
- Reflection methods for inverse problems with application to protein conformation determination
- The Block-wise Circumcentered-Reflection Method
- A feasibility approach for constructing combinatorial designs of circulant type
- A Lyapunov function construction for a non-convex Douglas-Rachford iteration
- Linear Convergence of the Douglas-Rachford Method for Two Closed Sets
- A Douglas-Rachford construction of non-separable continuous compactly supported multidimensional wavelets
- On the order of the operators in the Douglas-Rachford algorithm
- Anderson Acceleration for Nonconvex ADMM Based on Douglas-Rachford Splitting
- Solving graph coloring problems with the Douglas-Rachford algorithm
- Projection methods in quantum information science
- Norm Convergence of Realistic Projection and Reflection Methods
- Matrix product constraints by projection methods
- A parameterized Douglas-Rachford Splitting algorithm for nonconvex optimization
- New Douglas-Rachford algorithmic structures and their convergence analyses
- Fixed points of compositions of nonexpansive mappings: finitely many linear reflectors