A Novel Approach to Combine a SLS- and a DPLL-Solver for the Satisfiability Problem

Balint, Adrian; Henn, Michael; Gableske, Oliver

doi:10.1007/978-3-642-02777-2_28

Cited by 18 publications

(12 citation statements)

References 14 publications

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“…ADAPTG2 [24] • two recent hybrid methods submitted at the last SAT competition in 2009: 1. HYBRIDGM [2] 2. HYBRID1 [24] • and two complete methods:…”

Section: Methodsmentioning

confidence: 99%

Integrating Conflict Driven Clause Learning to Local Search

Audenard

Lagniez

Mazure

et al. 2009

Electron. Proc. Theor. Comput. Sci.

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This article introduces SatHyS (SAT HYbrid Solver), a novel hybrid approach for propositional satisfiability. It combines local search and conflict driven clause learning (CDCL) scheme. Each time the local search part reaches a local minimum, the CDCL is launched. For SAT problems it behaves like a tabu list, whereas for UNSAT ones, the CDCL part tries to focus on minimum unsatisfiable sub-formula (MUS). Experimental results show good performances on many classes of SAT instances from the last SAT competitions

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“…ADAPTG2 [24] • two recent hybrid methods submitted at the last SAT competition in 2009: 1. HYBRIDGM [2] 2. HYBRID1 [24] • and two complete methods:…”

Section: Methodsmentioning

confidence: 99%

Integrating Conflict Driven Clause Learning to Local Search

Audenard

Lagniez

Mazure

et al. 2009

Electron. Proc. Theor. Comput. Sci.

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“…NP-complete computation can be accelerated by developing faster algorithms for single machines and small clusters [5], [31], [35], [45]. Such work is complementary to ours since sTile is based on a Turing-universal computational model [6], [37] and can implement each of these advanced algorithms on large distributed networks.…”

Section: Related Workmentioning

confidence: 99%

Entrusting Private Computation and Data to Untrusted Networks

Brun

Medvidović

2013

IEEE Trans. Dependable and Secure Comput.

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Abstract-We present sTile, a technique for distributing trust-needing computation onto insecure networks, while providing probabilistic guarantees that malicious agents that compromise parts of the network cannot learn private data. With sTile, we explore the fundamental cost of achieving privacy through data distribution and bound how much less efficient a privacy-preserving system is than a nonprivate one. This paper focuses specifically on NP-complete problems and demonstrates how sTile-based systems can solve important real-world problems, such as protein folding, image recognition, and resource allocation. We present the algorithms involved in sTile and formally prove that sTile-based systems preserve privacy. We develop a reference sTile-based implementation and empirically evaluate it on several physical networks of varying sizes, including the globally distributed PlanetLab testbed. Our analysis demonstrates sTile's scalability and ability to handle varying network delay, as well as verifies that problems requiring privacypreservation can be solved using sTile orders of magnitude faster than using today's state-of-the-art alternatives.

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“…HybridGM (Balint et al, 2009) is an example of such algorithms. HybridGM is an incomplete hybrid SAT solver that combines local search and the Davis, Logemann and Loveland procedure.…”

Section: Hybrid Algorithmsmentioning

confidence: 99%

“…HybridGM is an incomplete hybrid SAT solver that combines local search and the Davis, Logemann and Loveland procedure. The local search solver gets supported by the Davis, Logemann and Loveland procedure to boost its performance (Balint et al, 2009). Other hybrid solvers can be found in , Crawford (1993), Ferris and Frohlich (2004), Gableske (2009), Havens and Dilkina (2004) and Habet et al (2002).…”

Section: Hybrid Algorithmsmentioning

confidence: 99%

A survey of the satisfiability-problems solving algorithms

Kilani

Bsoul

Alsarhan

et al. 2013

IJAIP

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The propositional satisfiability (SAT) problem is one of the most fundamental problems in computer science. SAT solvers have been successfully applied to a wide range of practical applications, including hardware model checking, software model finding, equivalence checking, and planning, among many others. Empirical research has been very fruitful for the development of efficient methods for SAT problems, such as classical Davis-Putnam method, greedy SAT (GSAT) method and neural network SAT method. This paper gives a survey about the methods used for solving the SAT problems with an emphasis on surveying the local search algorithms.

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A Novel Approach to Combine a SLS- and a DPLL-Solver for the Satisfiability Problem

Cited by 18 publications

References 14 publications

Integrating Conflict Driven Clause Learning to Local Search

Integrating Conflict Driven Clause Learning to Local Search

Entrusting Private Computation and Data to Untrusted Networks

A survey of the satisfiability-problems solving algorithms

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