Generating SAT instances with community structure
نویسندگان
چکیده
منابع مشابه
Generating SAT instances with community structure
Nowadays, modern SAT solvers are able to efficiently solve many industrial, or real-world, SAT instances. However, the process of development and testing of new SAT solving techniques is conditioned to the finite and reduced number of known industrial benchmarks. Therefore, new models of random SAT instances generation that capture realistically the features of real-world problems can be benefi...
متن کاملGenerating 'Random' 3-SAT Instances with Specific Solution Space Structure
Generating good benchmarks is important for the evaluation and improvement of any algorithm for NP-hard problems such as the Boolean satisfiability (SAT) problem. Carefully designed benchmarks are also helpful in the study of the nature of NP-completeness . Probably the most well-known and successful story is the discovery of the phase transition phenomenon (Cheeseman, Kanefsky, and Taylor 1991...
متن کاملCommunity Structure in Industrial SAT Instances
Modern SAT solvers have experienced a remarkable progress on solving industrial instances. Most of the techniques have been developed after an intensive experimental process. It is believed that these techniques exploit the underlying structure of industrial instances. However, there are few works trying to exactly characterize the main features of this structure. The research community on comp...
متن کاملGenerating SAT Instances from First-Order Formulas
To solve the satisfiability (SAT) problem in propositional logic, many algorithms have been proposed in recent years. However, practical problems are often more naturally described as satisfying a set of first-order formulas. When the domain of interpretation is finite and its size is a fixed positive integer, the satisfiability problem in the first-order logic can be reduced to SAT. To facilit...
متن کاملStructure features for SAT instances classification
The success of portfolio approaches in SAT solving relies on the observation that different SAT solvers may dramatically change their performance depending on the class of SAT instances they are trying to solve. In these approaches, a set of features of the problem is used to build a prediction model, which classifies instances into classes, and computes the fastest algorithm to solve each of t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 2016
ISSN: 0004-3702
DOI: 10.1016/j.artint.2016.06.001