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Fast immunized evolutionary programming

Authors: Wei Gao;

Fast immunized evolutionary programming

Abstract

Evolutionary programming is a good global optimization method. By introducing the improved adaptive mutation operation and improved selection operation based on thickness adjustment of artificial immune system into traditional evolutionary programming, a fast immunized evolutionary programming is proposed in this paper. At last, this algorithm is verified by simulation experiment of typical optimization function. The results of the experiment show that, the proposed fast immunized evolutionary programming can improve not only the convergent speed of original algorithm but also the computation effect of original algorithm, and is a very good optimization method.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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