automatic configuration of state-of-the-art multi-objective optimizers using the tp+pls framework
The automatic configuration of algorithms is a dynamic field of research. Its potential for producing highly performing algorithms may change the way we design algorithms. So far, automatic algorithm configuration tools have almost exclusively been applied to configure single-objective algorithms. In this paper, we investigate the usage of automatic algorithm configuration tools to improve multi-objective algorithms. In fact, this is the first article we are aware of where state-of-the-art multi-objective optimizers are configured in an automatic way. This automatic configuration is done for five variants of multi-objective flow-shop problems. Our experimental results show that we can reach at least the same and often a better final quality than a recently proposed state-of-the-art algorithm for these problems.
multi-objective flow-shop automatic configuration and tuning scheduling