摘要
高维连续函数的全局优化问题广泛存在于计算生物学、计算化学等诸多领域。针对这类问题,本文给出了一类改进的模拟退火算法,将局部极小化过程引入模拟退火算法。并采用一种简单的方法证明了该算法以概率1收敛于全局最优解。
The global optimization problems of continuous multi - dimension function frequently present in the fields of computational biology and computational chemistry. Regarding the characters of this class of problems, we add the local minimum to the simulated annealing algorithm. Its convergence properties are proved by using a simple approach, and we get the conclusion that the improved simulated annealing algorithm asymptotically converges to the global optimal solution in probability one.
关键词
连续函数
模拟退火算法
全局优化
局部极小化
收敛性
continuous function
simulated annealing algorithm
global optimization
local minimum
convergence property
