A faster dual algorithm for the Euclidean minimum covering ball problem

Published: 2017/06/30

Convex Optimization 1-center, computational geometry, minimum covering ball, minmax location, smallest enclosing ball Short URL: https://optimization-online.org/?p=14657

Dearing and Zeck presented a dual algorithm for the problem of the minimum covering ball in $\mathbb{R}^n$. Each iteration of their algorithm has a computational complexity of at least $\mathcal O(n^3)$. In this paper we propose a modification to their algorithm that, together with an implementation that uses updates to the QR factorization of a suitable matrix, achieves a $\mathcal O(n^2)$ iteration.

A faster dual algorithm for the Euclidean minimum covering ball problem

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