Forward-backward-half forward splitting algorithm with deviations
In this paper, we present a forward-backward-half forward splitting algorithm with deviations for solving the structured monotone inclusion problem composed of a maximally monotone operator, a maximally monotone and Lipschitz continuous operator and a cocoercive operator. The weak and linear converg...
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| Vydáno v: | Optimization Ročník 74; číslo 9; s. 2137 - 2158 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Taylor & Francis
04.07.2025
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| Témata: | |
| ISSN: | 0233-1934, 1029-4945 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | In this paper, we present a forward-backward-half forward splitting algorithm with deviations for solving the structured monotone inclusion problem composed of a maximally monotone operator, a maximally monotone and Lipschitz continuous operator and a cocoercive operator. The weak and linear convergence of the proposed algorithms is established. The aim of introducing deviations is to improve the performance of the forward-backward-half forward splitting algorithm through suitable choices of the deviations. A numerical example is given to show that the two-step inertial variant of the forward-backward-half forward splitting algorithms with deviations outperforms the existing methods in Briceño-Arias and Davis [Forward-backward-half forward algorithm for solving monotone inclusions, SIAM J Optimiz, 2017;28(4):2839-2871. doi:
10.1137/17M1120099
], Zong et al. [An accelerated forward-backward-half forward splitting algorithm for monotone inclusion with applications to image restoration, Optimization, 2022;73(2):401-428. doi:
10.1080/02331934.2022.2107926
] and Fan et al. [Convergence of an inertial shadow Douglas-Rachford splitting algorithm for monotone inclusions, Numer Func Anal Optim, 2021;42(14):1627-1644. doi:
10.1080/01630563.2021.2001749
]. |
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| ISSN: | 0233-1934 1029-4945 |
| DOI: | 10.1080/02331934.2024.2329271 |