Evolved preambles for MAX-SAT heuristics
Artificial Intelligence
2012-01-05 v1 Neural and Evolutionary Computing
Abstract
MAX-SAT heuristics normally operate from random initial truth assignments to the variables. We consider the use of what we call preambles, which are sequences of variables with corresponding single-variable assignment actions intended to be used to determine a more suitable initial truth assignment for a given problem instance and a given heuristic. For a number of well established MAX-SAT heuristics and benchmark instances, we demonstrate that preambles can be evolved by a genetic algorithm such that the heuristics are outperformed in a significant fraction of the cases.
Cite
@article{arxiv.1102.3868,
title = {Evolved preambles for MAX-SAT heuristics},
author = {Luis O. Rigo and Valmir C. Barbosa},
journal= {arXiv preprint arXiv:1102.3868},
year = {2012}
}