@inproceedings{950e686344ef49a7a591af23ec7449e1,
title = "Practical Performance of Random Projections in Linear Programming",
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.",
keywords = "Computational testing, Johnson-Lindenstrauss Lemma, Linear Programming",
author = "Leo Liberti and Benedetto Manca and Poirion, \{Pierre Louis\}",
note = "Publisher Copyright: {\textcopyright} Leo Liberti, Benedetto Manca, and Pierre-Louis Poirion; 20th International Symposium on Experimental Algorithms, SEA 2022 ; Conference date: 25-07-2022 Through 27-07-2022",
year = "2022",
month = jul,
day = "1",
doi = "10.4230/LIPIcs.SEA.2022.21",
language = "English",
series = "Leibniz International Proceedings in Informatics, LIPIcs",
publisher = "Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing",
editor = "Christian Schulz and Bora Ucar",
booktitle = "20th International Symposium on Experimental Algorithms, SEA 2022",
}