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Computational Experience with Rigorous Error Bounds for the Netlib Linear Programming Library
Citation Link: https://doi.org/10.15480/882.39
Publikationstyp
Preprint
Publikationsdatum
2005
Sprache
English
Institut
Citation
Reliable Computing, Volume 12, Issue 4, Pages 303 - 321
The Netlib library of linear programming problems is a well known suite containing many real world applications. Recently it was shown by Ordonez and Freund that 71% of these problems are ill-conditioned. Hence, numerical difficulties may occur. Here, we present rigorous results for this library that are computed by a verification method using interval arithmetic. In addition to the original input data of these problems we also consider interval input data. The computed rigorous bounds and the performance of the algorithms are related to the distance to the next ill-posed linear programming problem.
Schlagworte
Rigorose Fehlerschranken
linear programming, interval arithmetic, rigorous error bounds, sensitivity analysis, Netlib linear programming library
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