改进的蚁群算法及其在2DHP模型中的应用

Improved ACO for protein structure prediction using 2D HP lattice model

为了提高蛋白质折叠问题解的质量,采用蚁群算法对蛋白质的折叠问题进行研究,并且在现有的蚁群算法的基础上成功引入了淘汰和克隆机制,使其具有更好的运算效率,并成功应用到2DHP模型中。在蚁群对最优值进行搜索的过程中,容易出现局部最优点,导致影响解的质量。为了避免计算结果收敛到局部最优点,引入了一种最大最小蚁群策略。选择测试序列进行实验,实验结果表明,该算法在保证解的质量的同时,还具有较高的效率。

For improve the quality of solution to a Protein folding problem, ant colony optimization （ACO） is adopted to solve the protein folding simulations problem. Eliminate and clone based on the existing ACO is introduced. This ACO is applied in 2DHP model. At the same time, the ant colony will converge to local classic result easily when searching, and this process will infect the quality of the result. Avoiding the result converge to the local classic result, involving max-min ant colony. Choose some HP sequence for the experiment. And experiment proved that the improvement have higher efficiency than the older one when the two arithmetic got the same optimal solution.