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Main Authors: Burachik, Regina S., Caldwell, Bethany I., Kaya, C. Yalçın, Moursi, Walaa M., Saurette, Matthew
Format: Preprint
Published: 2022
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Online Access:https://arxiv.org/abs/2201.06661
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author Burachik, Regina S.
Caldwell, Bethany I.
Kaya, C. Yalçın
Moursi, Walaa M.
Saurette, Matthew
author_facet Burachik, Regina S.
Caldwell, Bethany I.
Kaya, C. Yalçın
Moursi, Walaa M.
Saurette, Matthew
contents The Douglas-Rachford and Peaceman-Rachford algorithms have been successfully employed to solve convex optimization problems, or more generally find zeros of monotone inclusions. Recently, the behaviour of these methods in the inconsistent case, i.e., in the absence of solutions has triggered significant consideration. It has been shown that under mild assumptions the shadow sequence of the Douglas-Rachford algorithm converges weakly to a generalized solution when the underlying operators are subdifferentials of proper lower semicontinuous convex functions. However, no convergence behaviour has been proved in the case of Peaceman-Rachford algorithm. In this paper, we prove the convergence of the shadow sequences associated with the Douglas-Rachford algorithm and Peaceman-Rachford algorithm when one of the operators is uniformly monotone and $3^*$ monotone but not necessarily a subdifferential. Several examples illustrate and strengthen our conclusion. We carry out numerical experiments using example instances of optimization problems.
format Preprint
id arxiv_https___arxiv_org_abs_2201_06661
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle On the Douglas-Rachford and Peaceman-Rachford algorithms in the presence of uniform monotonicity and the absence of minimizers
Burachik, Regina S.
Caldwell, Bethany I.
Kaya, C. Yalçın
Moursi, Walaa M.
Saurette, Matthew
Optimization and Control
Primary 49M27, 65K10, 90C25, Secondary 47H14, 49M29
The Douglas-Rachford and Peaceman-Rachford algorithms have been successfully employed to solve convex optimization problems, or more generally find zeros of monotone inclusions. Recently, the behaviour of these methods in the inconsistent case, i.e., in the absence of solutions has triggered significant consideration. It has been shown that under mild assumptions the shadow sequence of the Douglas-Rachford algorithm converges weakly to a generalized solution when the underlying operators are subdifferentials of proper lower semicontinuous convex functions. However, no convergence behaviour has been proved in the case of Peaceman-Rachford algorithm. In this paper, we prove the convergence of the shadow sequences associated with the Douglas-Rachford algorithm and Peaceman-Rachford algorithm when one of the operators is uniformly monotone and $3^*$ monotone but not necessarily a subdifferential. Several examples illustrate and strengthen our conclusion. We carry out numerical experiments using example instances of optimization problems.
title On the Douglas-Rachford and Peaceman-Rachford algorithms in the presence of uniform monotonicity and the absence of minimizers
topic Optimization and Control
Primary 49M27, 65K10, 90C25, Secondary 47H14, 49M29
url https://arxiv.org/abs/2201.06661