Boosting evolutionary algorithm configuration

Abstract

Algorithm configuration has emerged as an essential technology for the improvement of high-performance solvers. We present new algorithmic ideas to improve state-of-the-art solver configurators automatically by tuning. Particularly, we introduce 1. a forward-simulation method to improve parallel performance, 2. an improvement to the configuration process itself, and 3. a new technique for instance-specific solver configuration. Extensive experimental results show that the new solver configurator compares very favorably with the state-of-the-art in automatic configuration for combinatorial solvers.