Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Models for iterative global optimization
Models for iterative global optimization
A machine program for theorem-proving
Communications of the ACM
Phase Transitions and Backbones of 3-SAT and Maximum 3-SAT
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
An adaptive noise mechanism for walkSAT
Eighteenth national conference on Artificial intelligence
Where the really hard problems are
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
A backbone-search heuristic for efficient solving of hard 3-SAT formulae
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Evidence for invariants in local search
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
A two-phase backbone-based search heuristic for partial MAX-SAT: an initial investigation
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Automated reformulation of specifications by safe delay of constraints
Artificial Intelligence
Finding critical backbone structures with genetic algorithms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Data reductions, fixed parameter tractability, and random weighted d-CNF satisfiability
Artificial Intelligence
Automated reformulation of specifications by safe delay of constraints
Artificial Intelligence
Approximate backbone based multilevel algorithm for next release problem
Proceedings of the 12th annual conference on Genetic and evolutionary computation
On Computing Backbones of Propositional Theories
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
SAT as an effective solving technology for constraint problems
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
A backbone-based co-evolutionary heuristic for partial MAX-SAT
EA'05 Proceedings of the 7th international conference on Artificial Evolution
Random walk with continuously smoothed variable weights
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
SAS+ planning as satisfiability
Journal of Artificial Intelligence Research
Reasoning over biological networks using maximum satisfiability
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Hyperplane initialized local search for MAXSAT
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Hi-index | 0.00 |
Maximum satisfiability (Max-SAT) is more general and more difficult to solve than satisfiability (SAT). In this paper, we first investigate the effectiveness of Walksat, one of the best local search algorithms designed for SAT, on Max-SAT. We show that Walksat is also effective on Max-SAT, while its effectiveness degrades as the problem is more constrained. We then develop a novel method that exploits the backbone information in the local minima from Walksat and applies the backbone information in different ways to improve the performance of the Walksat algorithm. We call our new algorithm backbone guided Walksat (BGWalksat). On large random SAT and Max-SAT problems as well as instances from the SATLIB, BGWalksat significantly improves Walksat's performance.