基于寿命特征的模糊遗传算法(英文)  

A Fuzzy Genetic Algorithm Based on Lifetime Feature

作　　者：欧卫华[1] 刘建国[1] 孙勇[1] 

机构地区：[1]怀化学院数学系,湖南怀化418008

出　　处：《怀化学院学报》2007年第11期34-38,共5页Journal of Huaihua University

基　　金：湖南省教育厅资助科研项目(07C507)

摘　　要：在知识发觉中遗传算法已经广泛应用于分类,模型选择和其它优化问题.但是它的行为和表现却直接受其输入参数值(如交叉概率和变异概率)的影响,不合理的参数设置通常会导致许多问题比如早熟问题.为此有的学者提出用自适应技术在算法过程中自适应调整这些参数,但这并未对遗传算法产生整体的改善,因为参数设置是依赖于具体问题的.提出了基于染色体个体寿命特征的遗传算法,用模糊逻辑控制器自适应调整交叉概率和变异概率.这个方法加强了遗传算法的全局搜索能力,很好的解决了早熟问题.将本算法和标准遗传算法及自适应遗传算法比较,仿真结果表明本算法在克服早熟问题上的明显优势.In knowledge discovery, Genetic algorithms have been used for classification, model selection and other optimization tasks. However, behavior and performance of genetic algorithms are. directly affected by the values of their input parameters, while poor parameter settings usually lead to several problems such as the premature convergence. Adaptive techniques have been suggested for adjusting the parameters in the process of running the genetic algorithms. None of these techniques have yet shown a significant overall improvement, since most of them remain domain- specific. In this paper, we attempt to improve the performance of genetic algorithms by providing a new feature - - - Lifetime. We use a Fuzzy Logic Controller to adapt the crossover probability and mutation probability as a function of the chromosomes age. This approach should enhance the exploration and exploitation capabilities of the algorithm, while reducing its rate of premature convergence. We have evaluated the proposed methodology on some benchmark problems by comparing its performance to the basic and adaptive genetic algorithms. The simulation results demonstrate a clear advantage of the proposed method over other adaptive techniques at the aspect of overcoming prematurc convergence problem.

关 键 词：模糊逻辑 遗传算法 寿命 自适应技术 早熟 

分 类 号：O24[理学—计算数学]