Kybernetika 58 no. 4, 578-592, 2022

Distributed optimization with inexact oracle

Kui Zhu, Yichen Zhang and Yutao TangDOI: 10.14736/kyb-2022-4-0578


In this paper, we study the distributed optimization problem using approximate first-order information. We suppose the agent can repeatedly call an inexact first-order oracle of each individual objective function and exchange information with its time-varying neighbors. We revisit the distributed subgradient method in this circumstance and show its suboptimality under square summable but not summable step sizes. We also present several conditions on the inexactness of the local oracles to ensure an exact convergence of the iterative sequences towards the global optimal solution. A numerical example is given to verify the efficiency of our algorithm.


distributed optimization, multi-agent network, inexact oracle, first-order method, time-varying topology


65K10, 93A16


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