Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Artificial Intelligence
The OPL optimization programming language
The OPL optimization programming language
Logic programs with stable model semantics as a constraint programming paradigm
Annals of Mathematics and Artificial Intelligence
On the Satisfiability of Symmetrical Constrained Satisfaction Problems
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
Using Auxiliary Variables and Implied Constraints to Model Non-Binary Problems
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Breaking Row and Column Symmetries in Matrix Models
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
A Dual Graph Translation of a Problem in 'Life'
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Breaking Instance-Independent Symmetries in Exact Graph Coloring
Proceedings of the conference on Design, automation and test in Europe - Volume 1
ASSAT: computing answer sets of a logic program by SAT solvers
Artificial Intelligence - Special issue on nonmonotonic reasoning
Constraint Lingo: towards high-level constraint programming
Software—Practice & Experience - Research Articles
A comparison of complete global optimization solvers
Mathematical Programming: Series A and B
Compiling problem specification into SAT
Artificial Intelligence - Special volume on reformulation
Automated reformulation of specifications by safe delay of constraints
Artificial Intelligence
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Exploiting functional dependencies in declarative problem specifications
Artificial Intelligence
USING A THEOREM PROVER FOR REASONING ON CONSTRAINT PROBLEMS
Applied Artificial Intelligence
Evaluating ASP and commercial solvers on the CSPLib
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
A comparison of CLP(FD) and ASP solutions to NP-Complete problems
ICLP'05 Proceedings of the 21st international conference on Logic Programming
SAT as an effective solving technology for constraint problems
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Detecting and breaking symmetries by reasoning on problem specifications
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
A unifying framework for structural properties of CSPs: definitions, complexity, tractabilit
Journal of Artificial Intelligence Research
A 25-year perspective on logic programming
Compiling finite domain constraints to sat with bee*
Theory and Practice of Logic Programming
Boolean equi-propagation for concise and efficient SAT encodings of combinatorial problems
Journal of Artificial Intelligence Research
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This paper deals with four solvers for combinatorial problems: the commercial state-of-the-art solver ILOG oplstudio, and the research answer set programming (ASP) systems dlv, smodels and cmodels. The first goal of this research is to evaluate the relative performance of such systems when used in a purely declarative way, using a reproducible and extensible experimental methodology. In particular, we consider a third-party problem library, i.e., the CSPLib, and uniform rules for modelling and instance selection. The second goal is to analyze the marginal effects of popular reformulation techniques on the various solving technologies. In particular, we consider structural symmetry breaking, the adoption of global constraints, and the addition of auxiliary predicates. Finally, we evaluate, on a subset of the problems, the impact of numbers and arithmetic constraints on the different solving technologies. Results show that there is not a single solver winning on all problems, and that reformulation is almost always beneficial: symmetry-breaking may be a good choice, but its complexity has to be carefully chosen, by taking into account also the particular solver used. Global constraints often, but not always, help opl, and the addition of auxiliary predicates is usually worth, especially when dealing with ASP solvers. Moreover, interesting synergies among the various modelling techniques exist.