Title of Poster / Presentation
Location
Portland State University, Portland, Oregon
Start Date
12-5-2015 11:00 AM
End Date
12-5-2015 1:00 PM
Subjects
Mathematical optimization, Convex functions
Abstract
The smallest intersecting ball problem involves finding the minimal radius necessary to intersect a collection of closed convex sets. This poster discusses relevant tools of convex optimization and explores three methods of finding the optimal solution: the subgradient method, log-exponential smoothing, and an original approach using target set expansion. A fourth algorithm based on weighted projections is given, but its convergence is yet unproven. Numerical tests and comparison between methods are also presented.
Persistent Identifier
http://archives.pdx.edu/ds/psu/15374
Included in
The Smallest Intersecting Ball Problem
Portland State University, Portland, Oregon
The smallest intersecting ball problem involves finding the minimal radius necessary to intersect a collection of closed convex sets. This poster discusses relevant tools of convex optimization and explores three methods of finding the optimal solution: the subgradient method, log-exponential smoothing, and an original approach using target set expansion. A fourth algorithm based on weighted projections is given, but its convergence is yet unproven. Numerical tests and comparison between methods are also presented.