We introduce a new jump strategy for look-ahead based satisfiability (Sat) solvers that aims to boost their performance on satisfiable formulae, while maintaining their behavior on unsatisfiable instances. Direction heuristics select which Boolean value to assign to a decision variable. They are used in various state-of-the-art Sat solvers and may bias the distribution of solutions in the search-tree. This bias can clearly be observed on hard random k-Sat formulae. While alternative jump / restart strategies are based on exploring a random new part of the search-tree, the proposed one examines a part that is more likely to contain a solution based on these observations. Experiments with - so-called distribution jumping - in the march ks Sat...
One typically proves infeasibility in satisfiability/constraint satisfaction (or optimality in integ...
Intensification and diversification are the key factors that control the performance of stochastic l...
Motivated by our own industrial users, we attack the following challenge that is crucial in many pra...
We introduce a new jump strategy for look-ahead based satisfiability (Sat) solvers that aims to boos...
AbstractNew heuristics and strategies have enabled major advancements in SAT solving in recent years...
Modern conflict-driven clause-learning SAT solvers routinely solve large real-world instances with m...
The satisfiability problem (Sat) lies at the core of the complexity theory. This is a decision probl...
International audienceThe performance of modern conflict-driven clause learning (CDCL) SAT solvers s...
Abstract. In recent years backtrack search algorithms for Propositional Satisfiability (SAT) have be...
AbstractThis paper proposes the utilization of randomized backtracking within complete backtrack sea...
We show that we can design and implement extremely efficient variable selection heuristics for SAT s...
Abstract. Backbone variables have the same assignment in all solutions to a given constraint satisfa...
Abstract. Motivated by our own industrial users, we attack the following challenge that is crucial i...
Propositional satisfiability (SAT) solving procedures (or SAT solvers) are used as efficient back-en...
Abstract. The DPL (Davis-Putnam-Logemann-Loveland) procedure is one of the most effective methods fo...
One typically proves infeasibility in satisfiability/constraint satisfaction (or optimality in integ...
Intensification and diversification are the key factors that control the performance of stochastic l...
Motivated by our own industrial users, we attack the following challenge that is crucial in many pra...
We introduce a new jump strategy for look-ahead based satisfiability (Sat) solvers that aims to boos...
AbstractNew heuristics and strategies have enabled major advancements in SAT solving in recent years...
Modern conflict-driven clause-learning SAT solvers routinely solve large real-world instances with m...
The satisfiability problem (Sat) lies at the core of the complexity theory. This is a decision probl...
International audienceThe performance of modern conflict-driven clause learning (CDCL) SAT solvers s...
Abstract. In recent years backtrack search algorithms for Propositional Satisfiability (SAT) have be...
AbstractThis paper proposes the utilization of randomized backtracking within complete backtrack sea...
We show that we can design and implement extremely efficient variable selection heuristics for SAT s...
Abstract. Backbone variables have the same assignment in all solutions to a given constraint satisfa...
Abstract. Motivated by our own industrial users, we attack the following challenge that is crucial i...
Propositional satisfiability (SAT) solving procedures (or SAT solvers) are used as efficient back-en...
Abstract. The DPL (Davis-Putnam-Logemann-Loveland) procedure is one of the most effective methods fo...
One typically proves infeasibility in satisfiability/constraint satisfaction (or optimality in integ...
Intensification and diversification are the key factors that control the performance of stochastic l...
Motivated by our own industrial users, we attack the following challenge that is crucial in many pra...