摘要
针对遗传算法求解函数优化问题时控制参数难于确定的问题,提出先将函数按地貌信息聚成不同类,按类给出最佳的控制参数指导知识的解决方案。本文以复杂二维函数优化为例,提取表达函数的地貌信息特征参数,采用模糊C均值法将其聚类,得到适于不同类函数的最佳控制参数的知识。该知识可以指导遗传算法以最佳的控制参数进行函数优化。本研究为获取遗传优化最佳控制参数提供了一种新方法。
With the aim of the problem difficult to determine suitable control parameters for using genetic algorithm to solve the function optimization,it is suggested that the function be first clustered into different types in accordance with the landscape information.So that the solution schemes of optimal control parameter guidance knowledge should be given according to the types.With the optimization of complex binary function as an example,this paper extracts the feature parameters of landscape information to express the function: the fuzzy C-means is adopted to cluster them so as to obtain the optimal control parameter knowledge suitable to different types of functions.This knowledge can guide the genetic algorithm to do the function optimization with the optimal control parameters and provide a new kind of method to obtain the optimal control parameters for genetic optimization.
出处
《西安理工大学学报》
CAS
北大核心
2010年第1期26-30,共5页
Journal of Xi'an University of Technology
基金
国家自然科学基金资助项目(60743009
60873035)
陕西省自然科学基金资助项目(2006F43)
关键词
遗传算法
参数优化
函数地貌
函数聚类
genetic algorithm
parameters setting
fitness landscape of function
functions cluster