一种高效的模拟退火全局优化算法

An Efficient Simulated Annealing Algorithm for Global Optimization

提出了一种确定模拟退火算法温度更新函数的启发式准则，构造了适当的产生随机向量的概率密度函数，应用该启发式准则导出了相应的温度更新函数。新的温度更新函数与退火时间的幂函数成反比，与优化问题的变量维数无关。数值计算结果表明。

A heuristic criterion for determining the temperature updating function of simulated annealing algorithm is proposed in this paper.An appropriate form of probability density function for generating the random vectors is constructed.The temperature updating function corresponding to the probability density function is derived by using the proposed heuristic criterion.The new temperature updating function derived is inversely proportional to a power function of the annealing time and is independent of the dimension of the optimization problems.The numerical computation results indicate that the simulated annealing algorithm with the new temperature updatng function and the corresponding probability density function can improve significantly the computational efficiency for solving the global optimization problems.