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A Class of Nonsmooth Convex Optimization Problems

In: Optimization on Solution Sets of Common Fixed Point Problems

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  • Alexander J. Zaslavski

    (Technion - Israel Institute of Technology)

Abstract

In this chapter we study the convergence of the projected subgradient method for a class of constrained optimization problems in a Hilbert space. For this class of problems, an objective function is assumed to be convex but a set of admissible points is not necessarily convex. Our goal is to obtain an 𝜖-approximate solution in the presence of computational errors, where 𝜖 is a given positive number.

Suggested Citation

  • Alexander J. Zaslavski, 2021. "A Class of Nonsmooth Convex Optimization Problems," Springer Optimization and Its Applications, in: Optimization on Solution Sets of Common Fixed Point Problems, chapter 0, pages 311-397, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-78849-0_9
    DOI: 10.1007/978-3-030-78849-0_9
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