A self-organization genetic algorithm with cycle mutation

  • Na Wang
  • , Jian Zhuang
  • , Haifeng Du
  • , Wang Sun'an Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, a mutation with cycle probability is designed by simulating the evolutionary rule of the earth creature, and a genetic algorithm based on the cycle mutation, presents the ability in improving search efficiency and overcoming premature to some extent. To further improve performance of the algorithm, the selection is mended according to the phenomena that optimum individual always plays a major role, and an improved cycle mutation genetic algorithm is proposed. The experiment results on the benchmark functions optimization show that exploration and exploitation of this algorithm is better than some well-known evolution algorithms and it is not sensitive to the initial population distribution.

Original languageEnglish
Title of host publicationProceedings - 20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08
Pages530-533
Number of pages4
DOIs
StatePublished - 2008
Event20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08 - Dayton, OH, United States
Duration: 3 Nov 20085 Nov 2008

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume2
ISSN (Print)1082-3409

Conference

Conference20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08
Country/TerritoryUnited States
CityDayton, OH
Period3/11/085/11/08

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