Self Adaptive Island GA

Exploration efficiency of GAs largely depends on parameter values. But, it is hard to manually adjust these values. To cope with this problem, several adaptive GAs which automatically adjust parameters have been proposed. However, most of the existing adaptive GAs can adapt only a few parameters at the same time. Although several adaptive GAs can adapt multiple parameters simultaneously, these algorithms require extremely large computation costs. In this paper, we propose Self Adaptive Island GA(SAIGA) which adapts four parameter values simultaneously while finding a solution to a problem. SAIGA is a kind of island GA, and it adapts parameter values using a similar mechanism to meta-GA. Throughout our evaluation experiments, we confirmed that our algorithm outperforms a simple GA using De Jong’s rational parameters, and has performance close to a simple GA using manually tuned parameter values.

• Type: Conference
• Year: 2003
• Where: CEC
• Authors: Takashima, E.,Murata, Y., Shibata, N., Ito, M.
• Keywords: Genetic Algorithms