摘要
在简要叙述智能优化方法中机制产生的原理和方式的基础上,引入了智能优化算法所应具有的2种基本属性——集聚性和弥散性.描述了二者与算法收敛性的关系,指出了二者对于分析和构造算法的重要性,并结合实例进行了分析.最后根据算法的集聚性与弥散性,从算法群体进化角度研究了算法中的机制融合方法并结合实例进行了说明.
On the basis of a brief analysis of principles and means for the generation of mechanisms in intelligent optimization, centralization and decentralization, that are basic properties of intelligent optimization, are introduced. The relationship between these two properties and convergence is described. The significance of these two properties to analysis and construction of algorithms is proposed. Finally, using an example based on the centralization and decentralization of intelligent optimization, the mechanism combination of algorithm is explored from the point of view of population evolution. The practical examples are given.
出处
《智能系统学报》
2007年第2期48-56,共9页
CAAI Transactions on Intelligent Systems
基金
国家自然科学基金资助项目(60374069)
高等学校优秀青年教师科研奖励计划(20010248)
关键词
智能优化方法
集聚性与弥散性
机制融合
算法进化
intelligent optimization
centralization and decentralization
mechanism combination
algorithm evolution
