Approximation Algorithms and Hardness for Domination with Propagation
نویسندگان
چکیده
منابع مشابه
Approximation Algorithms and Hardness for Domination with Propagation
The power dominating set (PDS) problem is the following extension of the well-known dominating set problem: find a smallest-size set of nodes S that power dominates all the nodes, where a node v is power dominated if (1) v is in S or v has a neighbor in S, or (2) v has a neighbor w such that w and all of its neighbors except v are power dominated. We show a hardness of approximation threshold o...
متن کاملDomination in graphs with bounded propagation: algorithms, formulations and hardness results
We introduce a hierarchy of problems between the Dominating Set problem and the Power Dominating Set (PDS) problem called the l-round power dominating set (l-round PDS, for short) problem. For l = 1, this is the Dominating Set problem, and for l ≥ n − 1, this is the PDS problem; here n denotes the number of nodes in the input graph. In PDS the goal is to find a minimum size set of nodes S that ...
متن کاملApproximation algorithms and the hardness of approximation
Chandra Chekuri (Dept. of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL), Joseph Cheriyan (Dept. of Combinatorics and Optimization, University of Waterloo, Waterloo, ON), Ryan O’Donnell (School of Computer Science, Carnegie Mellon University, Pittsburgh, PA), Mohammad R. Salavatipour (Dept. of Computing Science, University of Alberta, Edmonton, AL), David Williamson (...
متن کاملApproximation Algorithms and Hardness of Approximation
S (in alphabetic order by speaker surname) Speaker: Hyung-Chan An (EPFL, Lausanne) Title: LP-Based Algorithms for Capacitated Facility Location Abstract: Linear programming has played a key role in the study of algorithms for combinatorial optimization problems. In the field of approximation algorithms, this is well illustrated by the uncapacitated facility location problem. A variety of algori...
متن کاملApproximation Algorithms and Hardness of Approximation January
In the previous lecture we saw examples of greedy algorithms that made locally optimal decisions at each step to arrive at a solution that wasn’t too far from the optimal solution in the end. Specifically for the case of Set Cover we saw that this strategy leads to the best possible approximation algorithm we could hope for (unless NP ⊂ DTIME(n ), which is very unlikely). In general, we also no...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SIAM Journal on Discrete Mathematics
سال: 2009
ISSN: 0895-4801,1095-7146
DOI: 10.1137/06066672x