As one of the most robust global optimization methods, simulated annealing has received considerable attention with many variations that attempt to improve the cooling schedule. This paper introduces a variant of molecular dynamics-based simulated annealing that is useful for optimizing atomistic structures, and makes use of the heat capacity of the system, determined on the fly during optimization, to adaptively control the cooling rate. This adaptive cooling approach is demonstrated to be more computationally efficient than classical simulated annealing when applied to Lennard-Jones clusters. The increase in efficiency is approximately a factor of two for clusters with 25–40 atoms, and improves as the size of the system increases.

中文翻译：

---

具有自适应冷却速率的模拟退火。

作为最强大的全局优化方法之一，模拟退火已引起人们的广泛关注，其许多变化试图改善冷却进度。本文介绍了一种基于分子动力学的模拟退火变体，可用于优化原子结构，并利用系统在优化过程中动态确定的热容量来自适应控制冷却速率。当应用于Lennard-Jones群集时，这种自适应冷却方法被证明比经典的模拟退火算法具有更高的计算效率。对于具有25–40个原子的簇，效率的提高约为两倍，并且随着系统规模的增加而提高。