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Decentralized optimization with affine constraints over time-varying networks

Author

Listed:
  • Demyan Yarmoshik

    (Moscow Institute of Physics and Technology
    Institute for Information Transmission Problems)

  • Alexander Rogozin

    (Moscow Institute of Physics and Technology)

  • Alexander Gasnikov

    (Moscow Institute of Physics and Technology
    Skoltech
    Institute for Information Transmission Problems)

Abstract

The decentralized optimization paradigm assumes that each term of a finite-sum objective is privately stored by the corresponding agent. Agents are only allowed to communicate with their neighbors in the communication graph. We consider the case when the agents additionally have local affine constraints and the communication graph can change over time. We provide the first linearly convergent decentralized algorithm for time-varying networks by generalizing the optimal decentralized algorithm ADOM to the case of affine constraints. We show that its rate of convergence is optimal for first-order methods by providing the lower bounds for the number of communications and oracle calls.

Suggested Citation

  • Demyan Yarmoshik & Alexander Rogozin & Alexander Gasnikov, 2024. "Decentralized optimization with affine constraints over time-varying networks," Computational Management Science, Springer, vol. 21(1), pages 1-23, June.
    • Handle: RePEc:spr:comgts:v:21:y:2024:i:1:d:10.1007_s10287-023-00492-w
    DOI: 10.1007/s10287-023-00492-w
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    References listed on IDEAS

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    1. Li, Wenzhuo & Tang, Rui & Wang, Shengwei & Zheng, Zhuang, 2023. "An optimal design method for communication topology of wireless sensor networks to implement fully distributed optimal control in IoT-enabled smart buildings," Applied Energy, Elsevier, vol. 349(C).
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