Combining SAT solvers on discrete resources
We are interested in this work in solving efficiently a set of instances of the SAT problem using several solvers such as to minimize the total execution time. We propose two new approaches based on the usage of a representative benchmark of SAT instances. In the first approach, we improve a problem in multiple heuristics such as to reduce the number of unsolved SAT instances. The second approach extends a naive solution for combining SAT solvers in a parallel context in introducing the selection of a convenient set of SAT solvers. We study the theoretical properties of our approaches and realize many experiments using a benchmark of SAT instances. The obtained results show that it is interesting to combine SAT solvers for reducing the number of unsolved SAT instances and the mean execution time required to solve a set of SAT instances.