Practical Performance of Random Projections in Linear Programming

Benedetto Manca;
2022-01-01

Abstract

The use of random projections in mathematical programming allows standard solution algorithms to solve instances of much larger sizes, at least approximately. Approximation results have been derived in the relevant literature for many specific problems, as well as for several mathematical programming subclasses. Despite the theoretical developments, it is not always clear that random projections are actually useful in solving mathematical programs in practice. In this paper we provide a computational assessment of the application of random projections to linear programming.
2022
Inglese
International Symposium on Experimental Algorithms
233
15
2-s2.0-85130359874
20th International Symposium on Experimental Algorithms, SEA 2022
Comitato scientifico
25/07/2022-27/07/2022
Heidelberg, Germany
internazionale
scientifica
Linear programming; Johnson-Lindenstrauss Lemma; Computational testing
sì
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Liberti, Leo; Manca, Benedetto; Poirion, Pierre-Louis
273
3
4.1 Contributo in Atti di convegno
open
info:eu-repo/semantics/conferencePaper
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