摘要
提出了一种称为广义自适应遗传算法的快速遗传算法，它首先产生均匀分布的初始种群，其次根据种群模式的状况决定是否引入“高品质”移民，最后自适应地进行交换和变异运算。其搜索性和全局收敛性比现有的许多遣传算法都有明显的改善，并通过仿真说明了该改进遣传算法的有效性。
A fast genetic algorithm-GSAGA(generalized self-adaptive genetic algorithm) is presentedin this paper First,evenly distributed initial population is generated. Then, high quality immigrants areintroduced according to the condition ofthe population schema. Finally, crossover and mutation are operated onself-adaptively in GSAGA, the searching performance and global convergence are greatly improved comparedwith many existing genetic algorithms. Through emulation, the validity of this modified genetic algorithm isproved..
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
1999年第1期49-53,共5页
Journal of University of Electronic Science and Technology of China
基金
四川省应用基础研究基金
关键词
广义自适应
遗传算法
初始种群
移民
适应度函数
generalized self-adaptive
genetic algorithm, initial population
immigration, fitnessfunction
