String-Averaging Methods for Best Approximation to Common Fixed Point Sets of Operators: The Finite and Infinite Cases
Yair Censor, Ariel Nisenbaum

TL;DR
This paper develops and analyzes string-averaging algorithms for finding the closest point in the common fixed point set of multiple operators, extending existing methods to both finite and infinite operator families in Hilbert spaces.
Contribution
It introduces new string-averaging methods for the best approximation problem, unifying and generalizing several existing algorithms as special cases.
Findings
Proposed methods work for finite and infinite families of operators.
Established convergence of the algorithms under certain conditions.
Unified framework includes known algorithms as special cases.
Abstract
String-averaging is an algorithmic structure used when handling a family of operators in situations where the algorithm at hand requires to employ the operators in a specific order. Sequential orderings are well-known and a simultaneous order means that all operators are used simultaneously (in parallel). String-averaging allows to use strings of indices, constructed by subsets of the index set of all operators, to apply the operators along these strings and then to combine their end-points in some agreed manner to yield the next iterate of the algorithm. String-averaging methods were discussed and used for solving the common fixed point problem or its important special case of the convex feasibility problem. In this paper we propose and investigate string-averaging methods for the problem of best approximation to the common fixed point set of a family of operators. This problem…
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