Tracking extrema in dynamic environments. Angeline, P. J. In Evolutionary Programming VI, volume 1213, of Lecture Notes in Computer Science, pages 335--345, 1997. Springer Berlin / Heidelberg. ![Tracking extrema in dynamic environments [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Typical applications of evolutionary optimization involve the off-line approximation of extrema of static multi-modal functions. Methods which use a variety of techniques to self-adapt mutation parameters have been shown to be more successful than methods which do not use self-adaptation. For dynamic functions, the interest is not to obtain the extrema but to follow it as closely as possible. This paper compares the on-line extrema tracking performance of an evolutionary program without self-adaptation against an evolutionary program using a self-adaptive Gaussian update rule over a number of dynamics applied to a simple static function. The experiments demonstrate that for some dynamic functions, self-adaptation is effective while for others it is detrimental.
@inproceedings{angeline_tracking_1997,
series = {Lecture {Notes} in {Computer} {Science}},
title = {Tracking extrema in dynamic environments},
volume = {1213},
isbn = {978-3-540-62788-3},
url = {http://www.springerlink.com/content/mq65257r410q114h/},
doi = {10.1007/BFb0014823},
abstract = {Typical applications of evolutionary optimization involve the off-line approximation of extrema of static multi-modal functions. Methods which use a variety of techniques to self-adapt mutation parameters have been shown to be more successful than methods which do not use self-adaptation. For dynamic functions, the interest is not to obtain the extrema but to follow it as closely as possible. This paper compares the on-line extrema tracking performance of an evolutionary program without self-adaptation against an evolutionary program using a self-adaptive Gaussian update rule over a number of dynamics applied to a simple static function. The experiments demonstrate that for some dynamic functions, self-adaptation is effective while for others it is detrimental.},
booktitle = {Evolutionary {Programming} {VI}},
publisher = {Springer Berlin / Heidelberg},
author = {Angeline, Peter J.},
year = {1997},
pages = {335--345}
}
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