Finding all minimal unsatisfiable subsets
Proceedings of the 5th ACM SIGPLAN international conference on Principles and practice of declaritive programming
Approximating minimal unsatisfiable subformulae by means of adaptive core search
Discrete Applied Mathematics - The renesse issue on satisfiability
AMUSE: a minimally-unsatisfiable subformula extractor
Proceedings of the 41st annual Design Automation Conference
Local-search Extraction of MUSes
Constraints
Identifying conflicts in overconstrained temporal problems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Applying local search to disjunctive temporal problems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
On finding all minimally unsatisfiable subformulas
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Discovery of minimal unsatisfiable subsets of constraints using hitting set dualization
PADL'05 Proceedings of the 7th international conference on Practical Aspects of Declarative Languages
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Models are used in science and engineering for experimentation, analysis, model-based diagnosis, design and planning/sheduling applications. Many of these models are overconstrained Numeric Constraint Satisfaction Problems (NCSP), where the numeric constraints could have linear or polynomial relations. In practical scenarios, it is very useful to know which parts of the overconstrained NCSP instances cause the unsolvability.Although there are algorithms to find all optimal solutions for this problem, they are computationally expensive, and hence may not be applicable to large and real-world problems. Our objective is to improve the performance of these algorithms for numeric domains using structural analysis. We provide experimental results showing that the use of the different strategies proposed leads to a substantially improved performance and it facilitates the application of solving larger and more realistic problems.