Generalized Self-Adaptive Genetic Al

时间:2023-04-30 06:38:23 数理化学论文 我要投稿
  • 相关推荐

Generalized Self-Adaptive Genetic Algorithms

In order to solve the problem between searching performance and convergence of genetic algorithms, a fast genetic algorithm-generalized self-adaptive genetic algorithm (GSAGA) is presented. (1) Evenlydistributed initial population is generated. (2) Superior individualsare not broken because of crossover and mutation operation for they are sent to subgeneration directly. (3) High quality immigrants are introduced according to the condition of the population schema. (4) Crossover and mutation are operated on self-adaptation. Therefore, GSAGA solves the coordination problem between convergence and searching performance. In GSAGA, the searching performance and global convergence are greatly improved compared with many existing genetic algorithms. Through simulation, the validity of this modified genetic algorithm is proved.

作 者: Bin Wu Xuyan Tu Jian Wu   作者单位: Bin Wu(Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China;Department of Information and Control Engineering,Southwest Instit ute of Technology,Mianyang 621002,China)

Xuyan Tu(Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China)

Jian Wu(Department of Information and Control Engineering,Southwest Instit ute of Technology,Mianyang 621002,China) 

刊 名: 北京科技大学学报(英文版)  EI SCI 英文刊名: JOURNAL OF UNIVERSITY OF SCIENCE AND TECHNOLOGY BEIJING  年,卷(期): 2000 7(1)  分类号: O22  关键词: generalized self-adaptive   genetic algorithm   initial population   immigration   fitness function  

【Generalized Self-Adaptive Genetic Al】相关文章:

The Caledonian low Al-TTD series from the Northern Qinling Orogenic Belt: Rock properties, genetic simulation and geolog04-29

The generalized solution of ill-posed boundary problem04-28

Slicing Recognition of Aircraft Integral Panel Generalized Pocket04-28

ASYMPTOTIC STABILITY OF RAREFACTION WAVE FOR GENERALIZED BURGERS EQUATION04-28

Underground water quality model inversion of genetic algorithm04-28

Generalized Method of Variational Analysis for 3-D Flow04-29

原位合成Al2O3/Ti-Al复合材料的研究04-27

ASYMPTOTIC NORMALITY OF QUASI MAXIMUM LIKELIHOOD ESTIMATE IN GENERALIZED LINEAR MODELS04-28

Genetic divergence among geographical populations of the migratory locust in China04-29

Al掺杂对尖晶石型Li[Mn(Al)]2O4结构的影响04-29