Beating the 'world champion' evolutionary algorithm via REVAC tuning

Abstract-- We present a case study demonstrating that using the REVAC parameter tuning method we can greatly improve the `world champion' EA (the winner of the CEC2005 competition) with little effort. For `normal' EAs the margins for possible improvements are likely much bigger. Thus, the main message of this paper is that using REVAC great performance improvements are possible for many EAs at moderate costs. Our experiments also disclose the existence of `specialized generalists', that is, EAs that are generally good on a set of test problems, but only w.r.t. one performance measure and not along another one. This shows that the notion of robust parameters is questionable and the issue requires further research. Finally, the results raise the question what the outcome of the CEC-2005 competition would have been, if all of EAs had been tuned by REVAC, but without further research it remains an open question whether we crowned the wrong king. I. BACKGROUND AND OBJECTIVES ...

• Type: Journal
• Year: 2010
• Where: CEC
• Authors: Selmar K. Smit, A. E. Eiben
• Keywords: Appropriate Parameter Values, Artificial Intelligence, CEC 2010, Mutation Rates, Parameter