מירב זהבי

אקדמי בכיר

A multivariate framework for weighted FPT algorithms

Hadas Shachnai, Meirav Zehavi

We introduce a multivariate approach for solving weighted parameterized problems. By allowing flexible use of parameters, our approach defines a framework for applying the classic bounded search trees technique. In our model, given an instance of size n of a minimization/maximization problem, and a parameter W≥1, we seek a solution of weight at most/at least W. We demonstrate the usefulness of our approach in solving VERTEX COVER, 3-HITTING SET, EDGE DOMINATING SET and MAX INTERNAL OUT-BRANCHING. While the best known algorithms for these problems admit running times of the form cWnO(1), for some c>1, our framework yields running times of the form csnO(1), where s≤W is the minimum size of a solution of weight at most/at least W. If no such solution exists, s=min⁡{W,m}, where m is the maximum size of a solution. In addition, we analyze the parameter t≤s, the minimum size of a solution.

שפת פרסום אנגלית
דפים 157-189
כתב עת Journal of Computer and System Sciences
כרך 89
סטטוס פרסום פורסם - 01.11.2017

Keywords

3-Hitting set
Edge dominating set
Parameterized algorithm
Vertex cover
Weighted graph problem

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science
Computer Networks and Communications
Computational Theory and Mathematics
Applied Mathematics
גישה למסמך
10.1016/j.jcss.2017.05.003
קבצים וקישורים אחרים
Link to publication in Scopus