Title
Adaptation Of Length In A Nonstationary Environment
Abstract
In this paper, we examine the behavior of a variable length GA in a nonstationary problem environment. Results indicate that a variable length GA is better able to adapt to changes than a fixed length GA. Closer examination of the evolutionary dynamics reveals that a variable length GA can in fact take advantage of its variable length representation to exploit good quality building blocks after a change in the problem environment. © Springer-Verlag Berlin Heidelberg 2003.
Publication Date
1-1-2003
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
2724
Number of Pages
1541-1553
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/3-540-45110-2_25
Copyright Status
Unknown
Socpus ID
35248831689 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/35248831689
STARS Citation
Yu, Han; Wu, Annie S.; and Lin, Kuo Chi, "Adaptation Of Length In A Nonstationary Environment" (2003). Scopus Export 2000s. 2005.
https://stars.library.ucf.edu/scopus2000/2005