Golden ratio annealing for satisfiability problems using dynamically cooling schemes

Authors:
Juan Frausto-Solis;Felix Martinez-Rios
Affiliations:
Tecnológico de Monterrey, Morelos, México;Universidad Panamericana, Distrito Federal, México
Venue:
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Year:
2008

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Abstract

Satisfiability (SAT) Problem is an NP-Complete problem which means no deterministic algorithm is able to solve it in a polynomial time. Simulated Annealing (SA) can find very good solutions of SAT instances if its control parameters are correctly tuned. SA can be tuned experimentally or by using a Markov approach; the latter has been shown to be the most efficient one. Moreover Golden Ratio (GR) is an unconventional technique used to solve many problems. In this paper a new algorithm named Golden Ratio for Simulated Annealing (GRSA) is presented; it is tuned for three different cooling schemes. GRSA uses GR to dynamically decrease the SA temperature and a Markov Model to tune its parameters. Two SA tuned versions are compared in this paper: GRSA and a classical SA. Experimentation shows that the former is much more efficient than the latter.