摘要
提出了一种基于数值编码的动态遗传算法．它采用实数值编码以解决待求解的精度受限问题，并引入独具特色的交叉和变异机制，有意识地引导交叉算子，最大限度地减少因变异盲目性导致的遗传基因丢失．此外，采用两个实例来验证算法的有效性和优越性．仿真结果表明：该算法可有效地实现快速全局寻优，并可有效地解决传统ＧＡ的饱和收敛问题．
おn this paper we propose a dynamic genetic algorithm based on numeric encoding.The numeric encoding can overcome the limitation of precision. The introduction of characteristic crossover and mutation mechanism can guide the crossover operaion consciously and decrease the loss of genes caused by aimlessness of mutation.This algorithm improves the speed of convergence of the solution and make the global optimal procedure more efficient.Furthermore,it successfully avoids the occurrence of premature converge.The validity and efficiency of the proposed algorithm are illustrated by two applications.
出处
《中南工业大学学报》
CSCD
北大核心
1998年第1期85-87,共3页
Journal of Central South University of Technology(Natural Science)
基金
国家自然科学基金
关键词
数值编码
交叉
变异
动态遗传算法
numeric encoding
crossover
mutation
dynamic genetic algorithm
