A straightforward local-search optimization algorithm on the symmetric group
classification
🧮 math.OC
keywords
algorithmgivengrouplocal-searchsymmetricvectoractsangle
read the original abstract
Given a real objective function defined over the symmetric group, a direct local-search algorithm is proposed, and its complexity is estimated. In particular for an $n$-dimensional unit vector we are interested in the permutation isometry that acts on this vector by mapping it into a cone of a given angle.
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