2010/11/26 by Olivier Bailleux, Bailleux, Olivier
Computer Science · #Advanced Database Systems and Queries #Constraint Satisfaction and Optimization #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Neural and Evolutionary Computing (cs.NE) #Semantic Web and Ontologies #cs.LO #cs.NE
paper · pdf · doi:10.48550/arxiv.1011.5866
arxiv created 2010/11/26 · openalex publication_date 2010/11/26 · arxiv updated 2010/11/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose to use local search algorithms to produce SAT instances which are harder to solve than randomly generated k-CNF formulae. The first results, obtained with rudimentary search algorithms, show that the approach deserves further study. It could be used as a test of robustness for SAT solvers, and could help to investigate how branching heuristics, learning strategies, and other aspects of solvers impact there robustness.