Consensus-Based Event-Triggered Distributed Optimization for a Network of Agents With Cubic Objective Functions

IF 7.9 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-06-09 DOI:10.1109/TNSE.2025.3578140

Zarar Ahmed Malik;Muhammad Rehan;Waqas Ahmed;Ijaz Ahmed;Choon Ki Ahn

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引用次数: 0

Abstract

The conventional resource allocation methods, using a central node, are not resilient, owing to the failure of the central unit. An advanced solution is to apply distributed optimization by integrating intelligent nodes across a network. This paper deals with distributed optimization via the event-triggered (ET) consensus approach for nodes over a directed graph. An optimality condition for solving the optimization problem of a collective cubic objective function is provided. An optimization protocol for solving the optimization problem in a distributed manner by application of a nonlinear incremental cost (IC) consensus method is proposed. The analysis for the proposed optimization protocol has been attained by the Lyapunov function and the Lyapunov-Krasovskii functional to attain IC consensus and balance of supply-demand mismatch. In contrast to the existing works, the proposed approach (i) deals with an optimization problem for a combined cubic objective function, (ii) considers an ET mechanism for bandwitdth management, (iii) deals with a directed network topology (rather than an undirected graph), and (iv) incorporates the communication delay. Moreover, the elimination of Zeno behavior is ensured through the resultant approach. Finally, simulation experiments for the resource allocation in distributed generators of cubic objective functions are provided by considering the comparison with existing works and analysis of the presented methodology.

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基于共识的三次目标函数智能体网络事件触发分布式优化

使用中心节点的传统资源分配方法由于中心单元的失效而缺乏弹性。一种先进的解决方案是通过集成整个网络中的智能节点来应用分布式优化。本文通过事件触发（ET）共识方法研究了有向图上节点的分布式优化问题。给出了求解集体三次目标函数优化问题的最优性条件。提出了一种利用非线性增量成本（IC）一致性方法求解分布式优化问题的优化协议。利用Lyapunov函数和Lyapunov- krasovskii函数对所提出的优化方案进行了分析，以达到IC一致性和供需不匹配的平衡。与现有的工作相比，所提出的方法(i)处理组合三次目标函数的优化问题，（ii）考虑带宽管理的ET机制，（iii）处理有向网络拓扑（而不是无向图），以及（iv）合并通信延迟。此外，通过合成方法确保消除芝诺行为。最后，通过与已有文献的比较和对所提方法的分析，对三次目标函数分布式发生器中的资源分配进行了仿真实验。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.