Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy

This study aims to unravel the resource allocation problem (RAP) by using a consensus-based distributed optimization algorithm under dynamic event-triggered (DET) strategies. Firstly, based on the multi-agent consensus approach, a novel one-to-all DET strategy is presented to solve the RAP. Secondly...

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Detalles Bibliográficos
Autores principales: Guo, Feilong, Chen, Xinrui, Yue, Mengyao, Jiang, Haijun, Chen, Siyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378691/
https://www.ncbi.nlm.nih.gov/pubmed/37509966
http://dx.doi.org/10.3390/e25071019
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author Guo, Feilong
Chen, Xinrui
Yue, Mengyao
Jiang, Haijun
Chen, Siyu
author_facet Guo, Feilong
Chen, Xinrui
Yue, Mengyao
Jiang, Haijun
Chen, Siyu
author_sort Guo, Feilong
collection PubMed
description This study aims to unravel the resource allocation problem (RAP) by using a consensus-based distributed optimization algorithm under dynamic event-triggered (DET) strategies. Firstly, based on the multi-agent consensus approach, a novel one-to-all DET strategy is presented to solve the RAP. Secondly, the proposed one-to-all DET strategy is extended to a one-to-one DET strategy, where each agent transmits its state asynchronously to its neighbors. Furthermore, it is proven that the proposed two types of DET strategies do not have Zeno behavior. Finally, numerical simulations are provided to validate and illustrate the effectiveness of the theoretical results.
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spelling pubmed-103786912023-07-29 Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy Guo, Feilong Chen, Xinrui Yue, Mengyao Jiang, Haijun Chen, Siyu Entropy (Basel) Article This study aims to unravel the resource allocation problem (RAP) by using a consensus-based distributed optimization algorithm under dynamic event-triggered (DET) strategies. Firstly, based on the multi-agent consensus approach, a novel one-to-all DET strategy is presented to solve the RAP. Secondly, the proposed one-to-all DET strategy is extended to a one-to-one DET strategy, where each agent transmits its state asynchronously to its neighbors. Furthermore, it is proven that the proposed two types of DET strategies do not have Zeno behavior. Finally, numerical simulations are provided to validate and illustrate the effectiveness of the theoretical results. MDPI 2023-07-04 /pmc/articles/PMC10378691/ /pubmed/37509966 http://dx.doi.org/10.3390/e25071019 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Guo, Feilong
Chen, Xinrui
Yue, Mengyao
Jiang, Haijun
Chen, Siyu
Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy
title Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy
title_full Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy
title_fullStr Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy
title_full_unstemmed Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy
title_short Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy
title_sort distributed optimization for resource allocation problem with dynamic event-triggered strategy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378691/
https://www.ncbi.nlm.nih.gov/pubmed/37509966
http://dx.doi.org/10.3390/e25071019
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