DocumentCode
342668
Title
Some information theoretic results on evolutionary optimization
Author
English, Thomas M.
Author_Institution
Tom English Comput. Innovations, Lubbock, TX, USA
Volume
1
fYear
1999
fDate
1999
Abstract
The body of theoretical results regarding conservation of information (“no free lunch”) in optimization has not related directly to evolutionary computation. Prior work has assumed that an optimizer traverses a sequence of points in the domain of a function without revisiting points. The present work reduces the difference between theory and practice by a) allowing points to be revisited, b) reasoning about the set of visited points instead of the sequence, and c) considering the impact of bounded memory and revisited points upon optimizer performance. Fortuitously, this leads to clarification of the fundamental results in conservation of information. Although most work in this area emphasizes the futility of attempting to design a generally superior optimizer, the present work highlights possible constructive use of the theory in restricted problem domains
Keywords
evolutionary computation; information theory; search problems; bounded memory; conservation of information; evolutionary computation; evolutionary optimization; information theoretic results; optimization; optimizer performance; revisited points; Design optimization; Entropy; Evolutionary computation; Information resources; Machine learning; Random variables; Signal generators; Technological innovation; Testing; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on
Conference_Location
Washington, DC
Print_ISBN
0-7803-5536-9
Type
conf
DOI
10.1109/CEC.1999.782013
Filename
782013
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