AIMS Mathematics (Jun 2024)

Convergence of distributed approximate subgradient method for minimizing convex function with convex functional constraints

  • Jedsadapong Pioon ,
  • Narin Petrot ,
  • Nimit Nimana

DOI
https://doi.org/10.3934/math.2024934
Journal volume & issue
Vol. 9, no. 7
pp. 19154 – 19175

Abstract

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In this paper, we investigate the distributed approximate subgradient-type method for minimizing a sum of differentiable and non-differentiable convex functions subject to nondifferentiable convex functional constraints in a Euclidean space. We establish the convergence of the sequence generated by our method to an optimal solution of the problem under consideration. Moreover, we derive a convergence rate of order $ \mathcal{O}(N^{1-a}) $ for the objective function values, where $ a\in (0.5, 1) $. Finally, we provide a numerical example illustrating the effectiveness of the proposed method.

Keywords