Minimum-Volume Covering Ellipsoids: Improving the Efficiency of the Wolfe-Atwood Algorithm for Large-Scale Instances by Pooling and Batching

  • Jakub Kudela
Keywords: minimum-volume covering ellipsoid, Lowner-John ellipsoid, large-scale optimization, Wolfe-Atwood algorithm, pooling, batching

Abstract

The Minimum-Volume Covering Ellipsoid (MVCE) problem is an important optimization problem that comes up in various areas of engineering and statistics. In this paper, we improve the state-of-the-art Wolfe-Atwood algorithm for solving the MVCE problem with pooling and batching procedures. This implementation yields significant improvements on the runtime of the algorithm for large-scale instances of the MVCE problem, which is demonstrated on quite extensive computational experiments.

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Published
2019-12-20
How to Cite
[1]
KudelaJ. 2019. Minimum-Volume Covering Ellipsoids: Improving the Efficiency of the Wolfe-Atwood Algorithm for Large-Scale Instances by Pooling and Batching. MENDEL. 25, 2 (Dec. 2019), 19-26. DOI:https://doi.org/10.13164/mendel.2019.2.019.
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Articles