[1]蔡良伟.基于距离测度的实数编码自适应遗传退火算法[J].深圳大学学报理工版,2004,21(4):291-294.
 CAI Liang-wei.Real-coded adaptive genetic annealing algorithm based on distance measurement[J].Journal of Shenzhen University Science and Engineering,2004,21(4):291-294.
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基于距离测度的实数编码自适应遗传退火算法()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第21卷
期数:
2004年4期
页码:
291-294
栏目:
光电与信息工程
出版日期:
2004-10-30

文章信息/Info

Title:
Real-coded adaptive genetic annealing algorithm based on distance measurement
文章编号:
1000-2618(2004)04-0291-04
作者:
蔡良伟
深圳大学信息工程学院, 深圳518060
Author(s):
CAI Liang-wei
College of Information Engineering, Shenzhen University, Shenzhen 518060,P. R. China
关键词:
遗传算法模拟退火算法自适应
Keywords:
genetic algorithm simulated annealing algorithm adaptive
分类号:
TP 301.6
文献标志码:
A
摘要:
提出一种基于距离测度的实数编码自适应遗传退火算法,根据个体的距离密集度自适应地确定其交叉概率和变异概率.空间距离密集度越高的个体,其交叉概率和变异概率也越高.算法引入模拟退火机制,在遗传进化过程中的每一代,对最优个体进行邻域局部寻优,利用模拟退火进一步改善算法的收敛性能.对带边界约束函数优化问题进行了仿真计算,结果表明该算法有效.
Abstract:
A real-coded adaptive genetic annealing algorithm based on distance measurement is proposed in this paper and the probabilities of crossover and mutation are adaptively determined according to the distance density of chromosomes. Chromosomes with high space distance density have high crossover and mutation probabilities. Simulated annealing mechanism is introduced to do local-search for the best chromosome in every generation of the evolution process. This improves the convergence of the algorithm. This algorithm is used to solve function optimization problem with boundary constraints and computation results show that the algorithm is very effective.

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更新日期/Last Update: 2015-11-06