利用动量项改进模拟退火

M. Keikha
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引用次数: 22

摘要

模拟退火算法是一种重要的进化算法,在优化问题中有着广泛的应用。模拟退火主要有两个阶段,第一个阶段是退火计划,第二个阶段是接受概率函数。提出了三种退火调度方法和一种接受概率函数。利用加入动量项的思想,提高退火调度程序的速度和精度,防止接受概率函数值的极端变化。我提出的一些方法显示出良好的精度,其他方法比原始模拟退火算法中使用的原始函数在模拟退火算法的速度上有显着提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Simulated Annealing Using Momentum Terms
Simulated Annealing is one of the important evolutionary algorithms which can be used in many applications especially in optimization problems. Simulated Annealing has two main phases, the first one is annealing schedule and the second is acceptance probability function. I proposed three annealing schedule methods and one acceptance probability function. The idea of adding momentum terms was used to improve speed and accuracy of annealing schedulers and prevent extreme changes in values of acceptance probability function. Some of my proposed methods show a good accuracy and the others make significant improvement in the speed of simulated Annealing algorithms than the original functions which have been used in the original simulated annealing algorithm.
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