Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
A linear-time transformation of linear inequalities into conjunctive normal form
Information Processing Letters
GRASP: A Search Algorithm for Propositional Satisfiability
IEEE Transactions on Computers
Journal of the ACM (JACM)
On using satisfiability-based pruning techniques in covering algorithms
DATE '00 Proceedings of the conference on Design, automation and test in Europe
A machine program for theorem-proving
Communications of the ACM
A comparative study of two Boolean formulations of FPGA detailed routing constraints
Proceedings of the 2001 international symposium on Physical design
Complexity classifications of boolean constraint satisfaction problems
Complexity classifications of boolean constraint satisfaction problems
Proceedings of the 38th annual Design Automation Conference
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
SATIRE: a new incremental satisfiability engine
Proceedings of the 38th annual Design Automation Conference
sub-SAT: a formulation for relaxed boolean satisfiability with applications in routing
Proceedings of the 2002 international symposium on Physical design
Solving difficult SAT instances in the presence of symmetry
Proceedings of the 39th annual Design Automation Conference
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Efficient conflict driven learning in a boolean satisfiability solver
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
SATO: An Efficient Propositional Prover
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
A fast pseudo-boolean constraint solver
Proceedings of the 40th annual Design Automation Conference
Inference methods for a pseudo-boolean satisfiability solver
Eighteenth national conference on Artificial intelligence
BerkMin: A Fast and Robust Sat-Solver
Proceedings of the conference on Design, automation and test in Europe
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Solving linear pseudo-Boolean constraint problems with local search
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Satisfiability modulo the theory of costs: foundations and applications
TACAS'10 Proceedings of the 16th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Hi-index | 14.98 |
Optimized solvers for the Boolean Satisfiability (SAT) problem have many applications in areas such as hardware and software verification, FPGA routing, planning, etc. Further uses are complicated by the need to express "counting constraints" in conjunctive normal form (CNF). Expressing such constraints by pure CNF leads to more complex SAT instances. Alternatively, those constraints can be handled by Integer Linear Programming (ILP), but generic ILP solvers may ignore the Boolean nature of 0-1 variables. Therefore specialized 0-1 ILP solvers extend SAT solvers to handle these so-called "pseudo-Boolean" (PB) constraints.This work provides an update on the on-going competition between generic ILP techniques and specialized 0-1 ILP techniques. To make a fair comparison, we generalize recent ideas for fast SAT-solving to more general 0-1 ILP problems that may include counting constraints and optimization. This generalization is embodied in our PB constraint solver and optimizer PBS, which is compared with state-of-the-art CNF and generic ILP solvers. Another aspect of our comparison is evaluation on 0-1 ILP benchmarks that originate in Electronic Design Automation (EDA), but that cannot be directly solved by a SAT solver. Specifically, we solve instances of the Max-SAT and Max-ONEs optimization problems which seek to maximize the number of satisfied clauses and the "true" values over all satisfying assignments, respectively. Those problems have straightforward applications to SAT-based routing and are additionally important due to reductions from Max-Cut, Max-Clique, and Min Vertex Cover. Our experimental results show that specialized 0-1 techniques implemented in PBS tend to outperform generic ILP techniques on Boolean optimization problems as well as on general EDA SAT problems.