计算机科学 ›› 2018, Vol. 45 ›› Issue (1): 228-232.doi: 10.11896/j.issn.1002-137X.2018.01.040

• 网络与通信 • 上一篇    下一篇

切换网络分布式次梯度优化算法

李甲地,李德权   

  1. 安徽理工大学数学与大数据学院 安徽 淮南232001,安徽理工大学数学与大数据学院 安徽 淮南232001
  • 出版日期:2018-01-15 发布日期:2018-11-13
  • 基金资助:
    本文受国家自然科学基金项目(61472003),安徽省高校学科(专业)拔尖人才学术资助

Distributed Subgradient Optimization Algorithm for Multi-agent Switched Networks

LI Jia-di and LI De-quan   

  • Online:2018-01-15 Published:2018-11-13

摘要: 研究了切换网络的多个体分布式次梯度优化算法。在有向切换网络是周期强连通的且对应的邻接矩阵是随机的而非双随机的条件下,利用非二次李雅普诺夫函数方法证明了所提多个体分布式次梯度优化算法的收敛性。最后,通过仿真实例验证了所提算法的有效性。

关键词: 多个体网络,分布式优化,有向切换网络,非二次李雅普诺夫函数,次梯度算法

Abstract: This paper studied the distributed subgradient algorithm for mult-agent optimization problem over switched networks.By using the non-quadratic Lyapunov function method,we proved that the convergence of the proposed distributed optimization algorithm can still be guaranteed under the condition that the directed switched network is periodically strongly connected and the corresponding adjacency matrix is stochastic rather than doubly stochastic.Finally,a simulation example was given to demonstrate the effectiveness of the proposed optimization algorithm.

Key words: Multi-agent network,Distributed optimization,Directed switched network,Non-quadratic Lyapunov function,Subgradient algorithm

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