Title :
Combining cellular genetic algorithms and local search for solving satisfiability problems
Author :
Folino, Gianluigi ; Pizzuti, Clara ; Spezzano, Giandomenico
Author_Institution :
ISI, Calabria Univ., Italy
Abstract :
A new parallel hybrid method for solving the satisfiability problem that combines cellular genetic algorithms and the random walk (WSAT) strategy of GSAT is presented. The method, called CGWSAT, uses a cellular genetic algorithm to perform a global search on a random initial population of candidate solutions and a local selective generation of new strings. Global search is specialized in local search by adopting the WSAT strategy. CGWSAT has been implemented on a Meiko CS-2 parallel machine using a two-dimensional cellular automaton as a parallel computation model. The algorithm has been tested on randomly generated problems and some classes of problems from the DIMACS test set
Keywords :
cellular automata; computability; genetic algorithms; parallel algorithms; parallel machines; problem solving; search problems; 2D cellular automaton; CGWSAT; DIMACS test set; GSAT; Meiko CS-2 parallel machine; cellular genetic algorithms; global search; local search; parallel computation model; parallel hybrid method; random walk; satisfiability problem solving; strings; two-dimensional cellular automaton; Artificial intelligence; Automata; Computational modeling; Computer vision; Concurrent computing; Genetic algorithms; Logic design; Parallel machines; Search methods; Testing;
Conference_Titel :
Tools with Artificial Intelligence, 1998. Proceedings. Tenth IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
0-7803-5214-9
DOI :
10.1109/TAI.1998.744842
