DocumentCode
1441293
Title
Evolutionary search for low autocorrelated binary sequences
Author
Militzer, Burkhard ; Zamparelli, Michele ; Beule, Dieter
Author_Institution
Dept. of Phys., Illinois Univ., Urbana, IL, USA
Volume
2
Issue
1
fYear
1998
fDate
4/1/1998 12:00:00 AM
Firstpage
34
Lastpage
39
Abstract
The search for low autocorrelated binary sequences is a classical example of a discrete frustrated optimization problem. We demonstrate the efficiency of a class of evolutionary algorithms to tackle the problem. A suitable mutation operator using a preselection scheme is constructed, and the optimal parameters of the strategy are determined
Keywords
binary sequences; genetic algorithms; search problems; discrete frustrated optimization problem; evolutionary algorithms; evolutionary search; low autocorrelated binary sequences; mutation operator; preselection scheme; Autocorrelation; Binary sequences; Evolutionary computation; Genetic mutations; Helium; Land surface temperature; Needles; Radar applications; Stationary state; Traveling salesman problems;
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/4235.728212
Filename
728212
Link To Document