There are no CNF problems

Authors:
Peter J. Stuckey
Affiliations:
National ICT Australia, Victoria Laboratory, Department of Computing and Information Systems, University of Melbourne, Australia
Venue:
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
Year:
2013

Citing 10
Cited 1

Constraint satisfaction in logic programming

Constraint satisfaction in logic programming
Solving SAT and SAT Modulo Theories: From an abstract Davis--Putnam--Logemann--Loveland procedure to DPLL(T)

Journal of the ACM (JACM)
Propagation via lazy clause generation

Constraints
MiniZinc: towards a standard CP modelling language

CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Explaining the cumulative propagator

Constraints
Optimal carpet cutting

CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Solving constraint satisfaction problems with SAT modulo theories

Constraints
Maximising the net present value for resource-constrained project scheduling

CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Conflict directed lazy decomposition

CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Solving RCPSP/max by lazy clause generation

Journal of Scheduling

Abstract satisfaction

Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages

Quantified Score

Hi-index	0.00

Visualization

Abstract

SAT technology has improved rapidly in recent years, to the point now where it can solve CNF problems of immense size. But solving CNF problems ignores one important fact: there are NO problems that are originally CNF. All the CNF that SAT solvers tackle is the result of modelling some real world problem, and mapping the high-level constraints and decisions modelling the problem into clauses on binary variables. But by throwing away the high level view of the problem SAT solving may have lost a lot of important insight into how the problem is best solved. In this talk I will hope to persuade you that by keeping the original high level model of the problem one can realise immense benefits in solving hard real world problems.