TY - GEN
T1 - A self-organization genetic algorithm with cycle mutation
AU - Wang, Na
AU - Zhuang, Jian
AU - Du, Haifeng
AU - Sun'an Wang, Wang
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/57649183507
U2 - 10.1109/ICTAI.2008.30
DO - 10.1109/ICTAI.2008.30
M3 - 会议稿件
AN - SCOPUS:57649183507
SN - 9780769534404
T3 - Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
SP - 530
EP - 533
BT - Proceedings - 20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08
T2 - 20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08
Y2 - 3 November 2008 through 5 November 2008
ER -