On Computing the Shadows and Slices of Polytopes

Computer Science – Computational Complexity

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We study the projection of polytopes along $k$ orthogonal vectors for various input and output forms. We show that if $k$ is part of the input and we are interested in output-sensitive algorithms, then in most forms the problem is equivalent to enumerating vertices of polytopes, except in two where it is NP-hard. In two other forms the problem is trivial. We also review the complexity of computing projections when the projection directions are picked at random. For full-dimensional polytopes containing origin in the interior, projection is an operation dual to intersecting the polytope with a suitable hyperplane and so the results in this paper can be dualized by interchanging vertices with facets and projection with intersection. We would like to remark that even though most of the results in this paper do not appear to have been published before, they follow from straighforward reductions to other known results. The purpose of this paper is to serve as a reference to these results about the computational complexity of projection of polytopes onto affine subspaces.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

On Computing the Shadows and Slices of Polytopes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with On Computing the Shadows and Slices of Polytopes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On Computing the Shadows and Slices of Polytopes will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-728205

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.