Optimalsize problem kernels for $d$Hitting Set in linear time and space
Abstract
We improve two lineartime data reduction algorithms for the dHitting Set problem to work in linear space, thus obtaining the first algorithms for computing problem kernels of asymptotically optimal size $O(k^d)$ for dHitting Set in linear time and space. We experimentally compare the two algorithms to a classical data reduction algorithm of Weihe and evaluate their combinations.
 Publication:

arXiv eprints
 Pub Date:
 March 2020
 arXiv:
 arXiv:2003.04578
 Bibcode:
 2020arXiv200304578V
 Keywords:

 Computer Science  Data Structures and Algorithms;
 Computer Science  Discrete Mathematics;
 68Q25;
 F.2.2;
 G.2.1