摘要
把混沌引入各种传统的优化计算模型中以避免系统落入局部最优陷阱 ,是一种行之有效的方法 .本文提出一种利用混沌搜索一类组合优化问题最优解的模型 ,并对其进行了理论分析和数值模拟 .与混沌神经网络模型相比 ,本模型避免了模型参数选择的难题 ,具有实现方便 ,寻优效果好的优点 。
It is a good idea to merge chaos into various conventional optimal methods in order to escape from local minima. This paper proposes a chaotic optimization model for combinatorial optimization problems and theoretically expounds that the model is feasible. Compared with chaotic neural network models, the present model will avoid the parameter settings of chaotic neural network models which is often very difficult, so it is easy to operate. Moreover, it can get better results according to numerical simulation.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2001年第5期102-105,共4页
Systems Engineering-Theory & Practice
基金
国家自然科学基金 !( 79970 0 4 2 )
