Title :
Massively parallel evolution of SAT heuristics
Author :
Fukunaga, Alex S.
Author_Institution :
Tokyo Inst. of Technol., Tokyo
Abstract :
Recent work has shown that it is possible to evolve heuristics for solving propositional satisfiability (SAT) problems which are competitive with the best hand-coded heuristics. However, previous work was limited by the computational resources required in order to evolve successful heuristics. In this paper, we describe a massively parallel genetic programming system for evolving SAT heuristics. Runs using up to 5.5 CPU core years of computation were executed, and resulted in new SAT heuristics which significantly outperform hand-coded heuristics.
Keywords :
computability; genetic algorithms; parallel programming; SAT heuristics; parallel genetic programming; propositional satisfiability; Aggregates; Algorithm design and analysis; Clustering algorithms; Constraint optimization; Design optimization; Evolutionary computation; Genetic programming; Input variables; Testing; Upper bound;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983117
