Parallel hybrid method for SAT that couples genetic algorithms and local search

Author

Folino, Gianluigi ; Pizzuti, Clara ; Spezzano, Giandomenico

Author_Institution

Inst. of Syst., Nat. Res. Council, Italy

Volume

5

Issue

4

fYear

2001

fDate

8/1/2001 12:00:00 AM

Firstpage

323

Lastpage

334

Abstract

A parallel hybrid method for solving the satisfiability (SAT) problem that combines cellular genetic algorithms (GAs) and the random walk SAT (WSAT) strategy of greedy SAT (GSAT) is presented. The method, called cellular genetic WSAT (CGWSAT), uses a cellular GA to perform a global search from a random initial population of candidate solutions and a local selective generation of new strings. The global search is then specialized in local search by adopting the WSAT strategy. A main characteristic of the method is that it indirectly provides a parallel implementation of WSAT when the probability of crossover is set to zero. CGWSAT has been implemented on a Meiko CS-2 parallel machine using a 2D cellular automaton as a parallel computation model. The algorithm has been tested on randomly generated problems and some classes of problems from the DIMACS and SATLIB test set

Keywords

cellular automata; computability; genetic algorithms; parallel algorithms; probability; search problems; cellular automaton; cellular genetic algorithms; global search; greedy SAT; parallel computation model; probability; random walk SAT; satisfiability problem; Automata; Biological cells; Circuit testing; Computational modeling; Concurrent computing; Genetic algorithms; Genetic mutations; Helium; Parallel machines; Search methods;

fLanguage

English

Journal_Title

Evolutionary Computation, IEEE Transactions on

Publisher

ieee

ISSN

1089-778X

Type

jour

DOI

10.1109/4235.942527

Filename

942527