Generalized simulated annealing algorithms using Tsallis statistics: Application to conformational optimization of a tetrapeptide.
Generalized simulated annealing algorithms using Tsallis statistics: Application to conformational optimization of a tetrapeptide.
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DOI：
10.1103/physreve.53.r3055
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发表时间：
1996-04-01
期刊：
影响因子：
--
通讯作者：
Straub
中科院分区：
文献类型：
--
作者：
Andricioaei I;Straub
提出了一种基于Tsallis广义熵的MonteCarlo模拟退火算法。该算法遵循细节平衡，并在低温下简化为最速下降算法。四肽构象优化的应用表明，该算法是更有效地定位低能量最小比基于分子动力学或蒙特卡罗方法的标准模拟退火。
A Monte Carlo simulated annealing algorithm based on the generalized entropy of Tsallis is presented. The algorithm obeys detailed balance and reduces to a steepest descent algorithm at low temperatures. Application to the conformational optimization of a tetrapeptide demonstrates that the algorithm is more effective in locating low energy minima than standard simulated annealing based on molecular dynamics or Monte Carlo methods.