Analysis and extension of the Inc* on the satisfiability testing problem

M Bader-El-Den, R Poli - 2008 IEEE Congress on Evolutionary …, 2008 - ieeexplore.ieee.org
2008 IEEE Congress on Evolutionary Computation (IEEE World …, 2008ieeexplore.ieee.org
Inc* is a general algorithm that can be used in conjunction with any local search heuristic
and that has the potential to substantially improve the overall performance of the heuristic.
The general idea of the algorithm is the following. Rather than attempting to directly solve a
difficult problem, the algorithm dynamically chooses a smaller instance of the problem, and
then increases the size of the instance only after the previous simplified instances have
been solved, until the full size of the problem is reached. Genetic programming is used to …
Inc* is a general algorithm that can be used in conjunction with any local search heuristic and that has the potential to substantially improve the overall performance of the heuristic. The general idea of the algorithm is the following. Rather than attempting to directly solve a difficult problem, the algorithm dynamically chooses a smaller instance of the problem, and then increases the size of the instance only after the previous simplified instances have been solved, until the full size of the problem is reached. Genetic programming is used to discover new strategies for Inc*. Preliminary experiments on the satisfiability problem (SAT) problem have shown that Inc* is a competitive approach. In this paper we enhance Inc* and we experimentally test it on larger set of benchmarks, including big instances of SAT. Furthermore, we provide an analysis of the algorithmpsilas behaviour.
ieeexplore.ieee.org
Showing the best result for this search. See all results