摘要
退火算法(Anncaling Algorithm)是一种随机优化方法,它综合蒙特卡洛方法和确定式下山处理的优点来解决复杂的优化问题,使对解的搜寻在获得下山法的可靠性和速度的同时,尽量避免陷入局部最小的势阱。这一算法在货郎问题(TSP)、电路划分及布局布线,以及神经网络的训练过程等许多优化处理中得到了应用,并取得了比较成功的结果。本文分析了该算法的收敛性,并解释了退火处理中某些操作的原则。
The annealing algorithm is a stochastic optimization method which has attracted attention because of its success with certain difficult problems,including NP-hard combinatorial ones such as the travelling salesman(TSP),circuit placement and routing.It has also been applied to the learning phase of Neural Network.In this paper,the convergence of this widely used algorithm is analy- sed and the criteria of some operations in annealing process are explained.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
1991年第4期16-21,共6页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金
关键词
组合优化
退火算法
收敛性
combinatorial optimization
simulated annealing
convergence of algorithm
obiective function
