A Gender-Based Genetic Algorithm for the Automatic Configuration of Algorithms

A problem that is inherent to the development and efficient use of solvers is that of tuning parameters. The CP community has a long history of addressing this task automatically. We propose a robust, inherently parallel genetic algorithm for the problem of configuring solvers automatically. In order to cope with the high costs of evaluating the fitness of individuals, we introduce a gender separation whereby we apply different selection pressure on both genders. Experimental results on a selection of SAT solvers show significant performance and robustness gains over the current state-of-the-art in automatic algorithm configuration.

• Type: Conference
• Year: 2009
• Where: CP
• Authors: Carlos Ansótegui, Kevin Tierney, Meinolf Sellmann
• Keywords: Automatic Algorithm Configuration, CP 2009, Parallel Genetic Algorithm, Programming Languages, SAT Solvers