Subgradient method with feasible inexact projections for constrained convex optimization problems. (2nd December 2022)

• Record Type: Journal Article
• Authors: Aguiar, A. A.; Ferreira, O. P.; Prudente, L. F.
• Is Part Of: Optimization. Volume 71:Number 12(2022)
• Page Start: 3515
• Page End: 3537
• Publication Date: 2022-12-02
• Subjects: Subgradient method -- feasible inexact projection -- constrained convex optimization; Mathematical optimization -- Periodicals; 519.7
• DOI: 10.1080/02331934.2021.1902520
• Languages: English
• ISSNs: 0233-1934

Abstract

Abstract : 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.