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Introduction

In: Convex Optimization with Computational Errors

Author

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  • Alexander Zaslavski

    (Israel Institute of Technology)

Abstract

In this book we study the behavior of algorithms for constrained convex minimization problems in a Hilbert space. Our goal is to obtain a good approximate solution of the problem in the presence of computational errors. It is known that the algorithm generates a good approximate solution, if the sequence of computational errors is bounded from above by a small constant. In our study, presented in this book, we take into consideration the fact that for every algorithm its iteration consists of several steps and that computational errors for different steps are different, in general. In this chapter we discuss several algorithms which are studied in this book.

Suggested Citation

  • Alexander Zaslavski, 2020. "Introduction," Springer Optimization and Its Applications, in: Convex Optimization with Computational Errors, chapter 0, pages 1-24, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-37822-6_1
    DOI: 10.1007/978-3-030-37822-6_1
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