%0 Journal Article
%T Adaptive genetic algorithm based on distance measurement<br>一种基于距离测度的自适应遗传算法
%A SHEN Hong-lian
%A ZHANG Guo-li
%A LI Zhen-tao
%A WANG Shu-ling
%A NI Gui-bo
%A <br>申红莲
%A 张国立
%A 李振涛
%A 王淑玲
%A 倪桂博
%J 计算机应用
%D 2007
%I 
%X In order to increase convergence probability and evolving speed of the adaptive genetic annealing algorithm based on distance measurement, an improved algorithm was proposed. The algorithm defined the mutation probability according to distance density and fitness, adopted improved crossover and simulated aimealing operation. In addition, when population tended to be uniform, it reserved the best individual and reproduced other individuals. Applying the improved realcoded genetic algorithm based on distance measurement to function optimization problem with boundary constraints, the simulative results show that the improved algorithm is more effective in realizing the high convergence probability and rapid evolving speed.
%K Genetic Algorithm (GA)
%K simulated annealing algorithm
%K adaptive
%K distance density<br>遗传算法
%K 模拟退火算法
%K 自适应
%K 距离密集度
%K 距离测度
%K 自适应
%K 实数编码遗传算法
%K distance
%K measurement
%K based
%K genetic
%K algorithm
%K 结果
%K 仿真计算
%K 优化问题
%K 约束函数
%K 边界
%K 利用
%K 最优个体
%K 群体
%K 退火操作
%K 模拟
%K 交叉操作
%K 算术
%K 变异概率
%K 适应度
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD27430512E8661D466971238E&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=5D311CA918CA9A03&sid=E641A1E50E600569&eid=F3D9B969D1F8BD1F&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=12