A Lyapunov Function Construction for a Non-convex Douglas–Rachford Iteration

Ohad Giladi () and Björn S. Rüffer ()
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Ohad Giladi: University of Newcastle
Björn S. Rüffer: University of Newcastle

Journal of Optimization Theory and Applications, 2019, vol. 180, issue 3, No 3, 729-750

Abstract: Abstract While global convergence of the Douglas–Rachford iteration is often observed in applications, proving it is still limited to convex and a handful of other special cases. Lyapunov functions for difference inclusions provide not only global or local convergence certificates, but also imply robust stability, which means that the convergence is still guaranteed in the presence of persistent disturbances. In this work, a global Lyapunov function is constructed by combining known local Lyapunov functions for simpler, local subproblems via an explicit formula that depends on the problem parameters. Specifically, we consider the scenario, where one set consists of the union of two lines and the other set is a line, so that the two sets intersect in two distinct points. Locally, near each intersection point, the problem reduces to the intersection of just two lines, but globally the geometry is non-convex and the Douglas–Rachford operator multi-valued. Our approach is intended to be prototypical for addressing the convergence analysis of the Douglas–Rachford iteration in more complex geometries that can be approximated by polygonal sets through the combination of local, simple Lyapunov functions.

Keywords: Douglas–Rachford iteration; Lyapunov function; Robust $$\mathcal {KL}$$ KL -stability; Non-convex optimization; Global convergence; 47H10; 47J25; 37N40; 90C26 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10957-018-1405-3

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