An Accelerated Asynchronous Distributed Method for Convex Constrained Optimization Problems
An Accelerated Asynchronous Distributed Method for Convex Constrained Optimization Problems
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DOI：
10.1109/ciss56502.2023.10089633
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发表时间：
2023-02
期刊：
影响因子：
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通讯作者：
Nazanin Abolfazli;A. Jalilzadeh;E. Y. Hamedani
中科院分区：
文献类型：
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作者：
Nazanin Abolfazli;A. Jalilzadeh;E. Y. Hamedani
考虑一类具有局部非线性凸约束的多智能体协作共识优化问题，其中只有通过边连接的智能体可以直接通信，因此最优共识决策位于这些私有集的交集中.我们开发了一个异步分布式加速原对偶算法来解决所考虑的问题。该计划是第一个异步方法，这类问题的最佳收敛保证，据我们所知。特别是，我们提供了一个最佳的收敛速度为$\mathcal{O}（1/K）$的次优，不可行性和共识违反。
We consider a class of multi-agent cooperative consensus optimization problems with local nonlinear convex constraints where only those agents connected by an edge can directly communicate, hence, the optimal consensus decision lies in the intersection of these private sets. We develop an asynchronous distributed accelerated primal-dual algorithm to solve the considered problem. The proposed scheme is the first asynchronous method with an optimal convergence guarantee for this class of problems, to the best of our knowledge. In particular, we provide an optimal convergence rate of $\mathcal{O}(1/K)$ for suboptimality, infeasibility, and consensus violation.