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基于动态事件触发策略的资源分配问题的分布式优化

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

作者信息

Guo Feilong, Chen Xinrui, Yue Mengyao, Jiang Haijun, Chen Siyu

机构信息

College of Mathematics and System Sciences, Xinjiang University, Urumqi 830017, China.

出版信息

Entropy (Basel). 2023 Jul 4;25(7):1019. doi: 10.3390/e25071019.

DOI:10.3390/e25071019
PMID:37509966
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10378691/
Abstract

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.

摘要

本研究旨在通过在动态事件触发（DET）策略下使用基于共识的分布式优化算法来解决资源分配问题（RAP）。首先，基于多智能体共识方法，提出了一种新颖的一对多DET策略来解决RAP。其次，将所提出的一对多DET策略扩展为一对一DET策略，其中每个智能体将其状态异步传输给其邻居。此外，证明了所提出的两种类型的DET策略不存在芝诺行为。最后，提供了数值模拟以验证和说明理论结果的有效性。

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本文引用的文献

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