Quick start guide for ParamILS

Users can also choose from a multitude of optimization objectives, reaching from minimizing average runtime to maximizing median approximation qualities. ParamILS then executes algorithm A with different combinations of parameters on instances sampled from S, searching for the configuration that yields overall best performance across the benchmark problems. For details, see Frank Hutter, Holger Hoos, and Thomas Stützle. Automatic Algorithm Configuration based on Local Search. In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI-07). If you use ParamILS in your research, please cite this article.