Neutral offspring controlling operators in genetic programming

Authors:
Liang Zhang;Asoke K. Nandi
Affiliations:
Signal Processing and Communications Group, Department of Electrical Engineering and Electronics, The University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, UK;Signal Processing and Communications Group, Department of Electrical Engineering and Electronics, The University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, UK
Venue:
Pattern Recognition
Year:
2007

Citing 19
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Abstract

Code bloat, one of the main issues of genetic programming (GP), slows down the search process, destroys program structures, and exhausts computer resources. To deal with these issues, two kinds of neutral offspring controlling operators are proposed-non-neutral offspring (NNO) operators and non-larger neutral offspring (NLNO) operators. Two GP benchmark problems-symbolic regression and 11-multiplexer-are used to test the new operators. Experimental results indicate that NLNO is able to confine code bloat significantly and improve performance simultaneously, which NNO cannot do.