Iterative Splitting Methods for Stochastic Dynamic SVIs
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866908357475958784 |
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| author | Sababe, Saeed Hashemi Ghasab, Ehsan Lotfali |
| author_facet | Sababe, Saeed Hashemi Ghasab, Ehsan Lotfali |
| contents | This paper extends split variational inclusion problems to dynamic, stochastic, and multi-agent systems in Banach spaces. We propose novel iterative algorithms to handle stochastic noise, time-varying operators, and coupled variational inclusions. Leveraging advanced splitting techniques and self-adaptive rules, we establish weak convergence under minimal assumptions on operator monotonicity. Numerical experiments demonstrate the efficacy of our algorithms, particularly in resource allocation and optimization under uncertainty. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_06570 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Iterative Splitting Methods for Stochastic Dynamic SVIs Sababe, Saeed Hashemi Ghasab, Ehsan Lotfali Optimization and Control Functional Analysis This paper extends split variational inclusion problems to dynamic, stochastic, and multi-agent systems in Banach spaces. We propose novel iterative algorithms to handle stochastic noise, time-varying operators, and coupled variational inclusions. Leveraging advanced splitting techniques and self-adaptive rules, we establish weak convergence under minimal assumptions on operator monotonicity. Numerical experiments demonstrate the efficacy of our algorithms, particularly in resource allocation and optimization under uncertainty. |
| title | Iterative Splitting Methods for Stochastic Dynamic SVIs |
| topic | Optimization and Control Functional Analysis |
| url | https://arxiv.org/abs/2505.06570 |