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基于云模型的进化算法
引用本文:张光卫,何锐,刘禹,李德毅,陈桂生.基于云模型的进化算法[J].计算机学报,2008,31(7).
作者姓名:张光卫  何锐  刘禹  李德毅  陈桂生
作者单位:1. 北京航空航天大学计算机学院,北京,100083
2. 中国电子系统工程研究所,北京,100840
基金项目:国家自然科学基金 , 国家重点基础研究发展计划(973计划)
摘    要:基于云模型在非规范知识的定性、定量表示及其相互转换过程中的优良特征,结合进化计算的基本思想,提出一种基于云模型的进化算法.该算法利用云模型对物种的遗传变异进化统一建模,能够自适应控制遗传变异的程度和搜索空间的范围,从而可以快速收敛到最优解,较好地避免了传统遗传算法易陷入局部最优解和选择压力过大造成的早熟收敛等问题.仿真结果表明:该算法具有精度高、收敛速度快等优点.云模型和进化计算思想的有效结合一方面拓宽了云模型的应用领域,也为进化计算的研究进行了新的探索和尝试.

关 键 词:云模型  进化计算  遗传算法  数值优化  人工智能

An Evolutionary Algorithm Based on Cloud Model
ZHANG Guang-Wei,HE Rui,LIU Yu,LI De-Yi,CHEN Gui-Sheng.An Evolutionary Algorithm Based on Cloud Model[J].Chinese Journal of Computers,2008,31(7).
Authors:ZHANG Guang-Wei  HE Rui  LIU Yu  LI De-Yi  CHEN Gui-Sheng
Abstract:Based on the outstanding characteristics of the cloud model on the process of transforming a qualitative concept to a set of quantitative numerical values,and integrating with the basic principle of evolutionary computation,the authors propose a novel rapid evolutionary algorithm,namely Cloud Model Based Evolutionary Algorithm or CBEA for short.With the cloud model,inheritance and mutation of species can be modeled naturally and uniformly,which make it easy and nature to control the scale of mutation and inheritance,and the scope of searching space.This enables CBEA to be able to find accurate numerical solutions within a short time.Numerical optimization experiments are carried out to verify the algorithm.With some of the typical test functions,the performance of CBEA is studies and also be compared with other algorithms.The results prove the high quality of the algorithm on precision,stability and convergence rate.In addition,the successful integrating of the cloud model and evolution principle expands the research fields of Cloud Theory and also indicates a new way for the research of evolutionary computation.
Keywords:cloud model  evolutionary computation  genetic algorithm  numerical optimization  artificial intelligence
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