Global behavior of the Douglas–Rachford method for a nonconvex feasibility problem

FJ Aragón Artacho, JM Borwein, MK Tam - Journal of Global Optimization, 2016 - Springer
Journal of Global Optimization, 2016Springer
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
many of these problems current theory is not sufficient to explain this observed success and
is mainly concerned with questions of local convergence. In this paper we analyze global
behavior of the method for finding a point in the intersection of a half-space and a potentially
non-convex set which is assumed to satisfy a well-quasi-ordering property or a property …
Abstract
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 many of these problems current theory is not sufficient to explain this observed success and is mainly concerned with questions of local convergence. In this paper we analyze global behavior of the method for finding a point in the intersection of a half-space and a potentially non-convex set which is assumed to satisfy a well-quasi-ordering property or a property weaker than compactness. In particular, the special case in which the second set is finite is covered by our framework and provides a prototypical setting for combinatorial optimization problems.
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