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The minimum covering Euclidean ball of a set of Euclidean balls in $$I\!\!R^n$$ I R n

P. M. Dearing () and Mark E. Cawood ()
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P. M. Dearing: Clemson University
Mark E. Cawood: Clemson University

Annals of Operations Research, 2023, vol. 322, issue 2, No 4, 659 pages

Abstract: Abstract Primal and dual algorithms are developed for solving the n-dimensional convex optimization problem of finding the Euclidean ball of minimum radius that covers m given Euclidean balls, each with given center and radius. Each algorithm is based on a directional search method in which a search path may be a ray or a two-dimensional conic section in $$I\!\!R^n$$ I R n . At each iteration, a search path is constructed by the intersection of bisectors of pairs of points, where the bisectors are either hyperplanes or n-dimensional hyperboloids. The optimal stopping point along each search path is determined explicitly.

Keywords: Location; Convex programming; Minimum covering ball; One-center location; Min–max location (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-022-05138-9

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