Paper Info
Title
Auto-Walksat: A Self-Tuning Implementation of Walksat
Abstract
Abstract Stochastic search algorithms have proven to be very fast at solving many satisfiability problems [2,3,8]. The nature of their search requires careful parameter tuning to maximize performance, but depending on the problem and the details of the stochastic algorithm, the correct tuning may be difficult to ascertain [9]. In this paper we introduce Auto-Walksat , a general algorithm which automatically tunes any variant of the Walksat family of stochastic satisfiability solvers. We demonstrate Auto-Walksat's success in tuning Walksat-SKC to the DIMACS benchmark problems with negligible additional overhead.
Year
DOI
Venue
2001
10.1016/S1571-0653(04)00333-6
Electronic Notes in Discrete Mathematics
Keywords
Field
DocType
Satisfiability testing,invariant ratio,local search,stochastic algorithms,parameter tuning,Walksat,Auto-Walksat
WalkSAT,Stochastic algorithms,Discrete mathematics,Mathematical optimization,Combinatorics,Search algorithm,General algorithm,Satisfiability,Self-tuning,Local search (optimization),Mathematics
Journal
Volume
ISSN
Citations 
9
1571-0653
18
PageRank 
References 
Authors
1.18
6
2
Name
Order
Citations
PageRank
Donald J. Patterson11765219.99
Henry A. Kautz292711010.27