摘要
随机扩散搜索法作为一种群智能算法,其显著特征是部分函数评价和一对一的征兵机制,这些特点使得随机扩散搜索法运算效率高且鲁棒性好.本文在对随机扩散搜索法的基本原理和研究现状综述的基础上,对其存在的问题及特点进行分析,并对未来的研究提出一些建议.
As one of swarm intelligence optimization algorithms, the stochastic diffusion search is characterized by partial function evaluation and one-to-one recruitment mechanism, These characteristics make the algorithm high computation efficiency and robustness of the stochastic diffusion search. Based on the survey of basic principles and the research actuality of stochastic diffusion search, the existing problem and features are analyzed, and some future research directions about the stochastic diffusion search are delineated.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2008年第3期351-356,共6页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金资助项目(No.60674104)
关键词
随机扩散搜索法(SDS)
群智能优化算法
部分函数评价
一对一征兵机制
Stochastic Diffusion Search ( SDS Function Evaluation, One-To-One ), Swarm Intelligence Optimization Algorithm, Partial Recruitment Mechanism