On the Effectiveness of Projection Methods for Convex Feasibility Problems with Linear Inequality Constraints
For practitioners solving large-scale linear inequality systems, the paper provides evidence that projection methods are computationally advantageous.
The paper demonstrates that projection methods for solving systems of linear inequalities have a computational advantage over alternatives, supported by experiments on problems with up to tens of thousands of unknowns and hundreds of thousands of constraints, and by evidence from applications with over a billion unknowns.
The effectiveness of projection methods for solving systems of linear inequalities is investigated. It is shown that they have a computational advantage over some alternatives and that this makes them successful in real-world applications. This is supported by experimental evidence provided in this paper on problems of various sizes (up to tens of thousands of unknowns satisfying up to hundreds of thousands of constraints) and by a discussion of the demonstrated efficacy of projection methods in numerous scientific publications and commercial patents (dealing with problems that can have over a billion unknowns and a similar number of constraints).