Subgradient method with feasible inexact projections for constrained convex optimization problems

In this paper, we propose a new inexact version of the projected subgradient method to solve nondifferentiable constrained convex optimization problems. The method combine ϵ-subgradient method with a procedure to obtain a feasible inexact projection onto the constraint set. Asymptotic convergence re...

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Bibliographic Details
Published inOptimization Vol. 71; no. 12; pp. 3515 - 3537
Main Authors Aguiar, A. A., Ferreira, O. P., Prudente, L. F.
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 02.12.2022
Taylor & Francis LLC
Subjects
constrained convex optimization
Constraints
Convexity
feasible inexact projection
Optimization
Subgradient method
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Summary:In this paper, we propose a new inexact version of the projected subgradient method to solve nondifferentiable constrained convex optimization problems. The method combine ϵ-subgradient method with a procedure to obtain a feasible inexact projection onto the constraint set. Asymptotic convergence results and iteration-complexity bounds for the sequence generated by the method employing the well-known exogenous stepsizes, Polyak's stepsizes, and dynamic stepsizes are established.
ISSN:0233-1934
1029-4945
DOI:10.1080/02331934.2021.1902520