Genetic algorithm and Tabu search based methods for molecular 3D-structure prediction
Genetic algorithm and Tabu search based methods for molecular 3D-structure prediction
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DOI：
10.3934/naco.2011.1.191
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发表时间：
2011-02
期刊：
影响因子：
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通讯作者：
A. Hedar;A. Ali;Taysir Hassan Abdel-Hamid
中科院分区：
文献类型：
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作者：
A. Hedar;A. Ali;Taysir Hassan Abdel-Hamid
寻找势能函数的全局最小值是非常困难的，因为局部最小值的数量随着分子大小呈指数增长。本文提出了遗传算法和禁忌搜索方法的应用，分别称为GAMCP (genetic algorithm with Matrix Coding Partitioning)[7]和TSVP (tabu search with Variable Partitioning)[8]，用于最小化分子势能函数。给出了在200个自由度范围内的问题的计算结果，并与文献中其他四种现有方法进行了比较。数值结果表明，这两种方法都具有较好的应用前景，计算成本低，求解质量高。
The search for the global minimum of a potential energy function is very difficult since the number of local minima grows exponentially with the molecule size. The present work proposes the application of genetic algorithm and tabu search methods, which are called GAMCP (Genetic Algorithm with Matrix Coding Partitioning) [7], and TSVP (Tabu Search with Variable Partitioning) [8], respectively, for minimizing the molecular potential energy function. Computational results for problems with up to 200 degrees of freedom are presented and are favorable compared with other four existing methods from the literature. Numerical results show that the proposed two methods are promising and produce high quality solutions with low computational costs.