DocumentCode
1638529
Title
Massively parallel evolution of SAT heuristics
Author
Fukunaga, Alex S.
Author_Institution
Tokyo Inst. of Technol., Tokyo
fYear
2009
Firstpage
1478
Lastpage
1485
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/CEC.2009.4983117
Filename
4983117
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