摘要
针对实数编码在进行数值优化时固有的过早收敛、停滞现象和弱的爬山能力等缺点,通过设计不同的交叉、变异算子,提出了一种改进的实数编码遗传算法。数值实验显示,该方法在函数优化问题上取得了非常满意的效果。
An improved real-code genetic algorithm is designed with different cross, selection and variation operators, aiming at overcoming its inherent shortcomings of premature, dead state convergence and weak mountain climbing during function optimization. Experiments shows the satisfactory effect of the improved algorithm.
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2004年第6期67-70,共4页
Journal of the China Railway Society
关键词
遗传算法
早熟现象
实数编码
函数优化
genetic algorithm
premature convergence
real-code
function optimization
