On the effectiveness of projection methods for convex feasibility problems with linear inequality constraints

Abstract : The effectiveness of projection methods for solving systems of linear inequalities is investigated. It is shown that they often have a computational advantage over alternatives that have been proposed for solving the same problem and that this makes them successful in many 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).
keyword : sadco
Type de document :
Article dans une revue
Computational Optimization and Applications, Springer Verlag, 2011, 〈10.1007/s10589-011-9401-7〉
Liste complète des métadonnées

https://hal.inria.fr/hal-00643783
Contributeur : Estelle Bouzat <>
Soumis le : mardi 22 novembre 2011 - 17:43:45
Dernière modification le : lundi 26 novembre 2018 - 01:19:57

Lien texte intégral

Identifiants

Collections

Citation

Yair Censor, Wei Chen, Patrick Louis Combettes, Ran Davidi, Gabor Herman. On the effectiveness of projection methods for convex feasibility problems with linear inequality constraints. Computational Optimization and Applications, Springer Verlag, 2011, 〈10.1007/s10589-011-9401-7〉. 〈hal-00643783〉

Partager

Métriques

Consultations de la notice

155