New factorial design theoretic crossover operator for parametrical problem

Chan, Kit Yan; Aydin, M. Emin; Fogarty, Terence C.

Abstract

Recent research shows that factorial design methods improve the performance of the crossover operator in evolutionary computation. However the methods employed so far ignore the effects of interaction between genes on fitness, i.e. "epistasis". Here we propose the application of a systematic method for interaction effect analysis to enhance the performance of the crossover operator. It is shown empirically that the proposed method significantly outperforms existing crossover operators on benchmark problems with nigh interaction between the variables. © Springer-Verlag Berlin Heidelberg 2003.

• Presentation Conference Type: Conference Paper (published)
• Online Publication Date: May 13, 2003
• Publication Date: 2003
• Deposit Date: Apr 30, 2021
• Publisher: Springer Verlag (Germany)
• Volume: 2610
• Pages: 22-33
• Series Title: Lecture Notes in Computer Science
• Book Title: Genetic Programming
• ISBN: 354000971X; 9783540009719
• DOI: https://doi.org/10.1007/3-540-36599-0_3
• Public URL: https://uwe-repository.worktribe.com/output/6545541