基于双阈值的具有记忆功能的自适应模拟退火算法

Adaptive Simulated Annealing Algorithm with Memory Function Based on Double Thresholds

讨论传统模拟退火算法的原理、求解过程,详细分析它存在的局限性,简单叙述模拟退火算法中关键参数对该算法性能的影响,并给出该算法的可行性改进方案。提出一个改进的模拟退火算法。在该改进算法中,为避免遗失当前最优解,增加记忆功能,将当前最好的状态记忆下来,从而使得模拟退火算法成为一种智能化算法;设计一个自适应温度更新函数,并设置双阈值使得在尽量保持最优性的前提下减少计算量。用改进前后的两个算法来解决一个非线性寻找组合最优问题,实验证明改进后的模拟退火算法是高效的。

It firstly introduced the traditional simulated annealing algorithm through discussing its theory and process, analyzed its shortcoming in detail, simply described influence of key parameters to simulated annealing algorithm and provid- ed feasible improvement. Then it presented a method of improving simulated annealing algorithm. In order to avoid missing current optimal solution, the improved algorithm is increased memory function to remember the current best state so that it becomes an intelligent algorithm. It also designed an adaptive temperature update function and set up dual-threshold to re- duce amount of calculation. Finally, it used the two algorithms to solve a no-linear problem that is searching optimization combination. Through testing, the improved simulated annealing algorithm is better than the traditional simulated annealing algorithm.