Projection Methods: An Annotated Bibliography of Books and Reviews
Yair Censor, Andrzej Cegielski

TL;DR
This paper provides an annotated bibliography of books and reviews on projection methods, highlighting their principles, algorithmic structures, convergence properties, and applications in optimization and scientific problems.
Contribution
It compiles and reviews key literature on projection methods, clarifying their definitions, types, and recent progress in the field.
Findings
Projection methods are effective for feasibility and optimization problems.
They have diverse algorithmic structures suitable for parallel computing.
Recent years have seen significant advancements and successful applications.
Abstract
Projections onto sets are used in a wide variety of methods in optimization theory but not every method that uses projections really belongs to the class of projection methods as we mean it here. Here projection methods are iterative algorithms that use projections onto sets while relying on the general principle that when a family of (usually closed and convex) sets is present then projections (or approximate projections) onto the given individual sets are easier to perform than projections onto other sets (intersections, image sets under some transformation, etc.) that are derived from the given family of individual sets. Projection methods employ projections (or approximate projections) onto convex sets in various ways. They may use different kinds of projections and, sometimes, even use different projections within the same algorithm. They serve to solve a variety of problems which…
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