Statistical optimisation and tuning of GA factors

This paper presents a practical methodology of improving the efficiency of Genetic Algorithms through tuning the factors significantly affecting GA performance. This methodology is based on the methods of statistical inference and has been successfully applied to both binary- and integerencoded Genetic Algorithms that search for good chemotherapeutic schedules.

• Type: Conference
• Year: 2005
• Where: CEC
• Authors: Andrei Petrovski, Alexander E. I. Brownlee, John A. W. McCall
• Keywords: Artificial Intelligence, CEC 2005, Genetic Algorithms, Integerencoded Genetic Algorithms, Practical Methodology