Year: 2010
Type: preprint
Abstract: The aim of this thesis is to determine classes of NP relations for which random generation and approximate counting problems admit an efficient solution. Since efficient rank implies efficient random generation, we first investigate some classes of NP relations admitting efficient ranking. On the other hand, there are situations in which efficient random generation is possible even when ranking is computationally infeasible. We introduce the notion of ambiguous description as a tool for random generation and approximate counting in such cases and show, in particular, some applications to the case of formal languages. Finally, we discuss a limit of an heuristic for combinatorial optimization problems based on the random initialization of local search algorithms showing that derandomizing such heuristic can be, in some cases, #P-hard.
Source: arXiv (Cornell University)
Author: Santini, Massimo
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1543075421