Distributed Event-Triggered Algorithm for Convex Optimization with Coupled Constraints

2022/10/26 by Yi Huang, Xianlin Zeng, Huang, Yi +5 · 1 citation
Computer Science · #Distributed Control Multi-Agent Systems #FOS: Mathematics #Optimization and Control (math.OC) #Optimization and Variational Analysis

paper · pdf · doi:10.48550/arxiv.2210.14415

openalex publication_date 2022/10/26 · openalex created_date 2022/11/02 · openalex updated_date 2026/07/28

Abstract

This paper develops a distributed primal-dual algorithm via event-triggered mechanism to solve a class of convex optimization problems subject to local set constraints, coupled equality and inequality constraints. Different from some existing distributed algorithms with the diminishing step-sizes, our algorithm uses the constant step-sizes, and is shown to achieve an exact convergence to an optimal solution with an O(1/k) convergence rate for general convex objective functions, where k>0 is the iteration number. Moreover, by applying event-triggered communication mechanism, the proposed algorithm can effectively reduce the communication cost without sacrificing the convergence rate. Finally, a numerical example is presented to verify the effectiveness of the proposed algorithm.

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