摘要
针对蛋白质折叠问题的二维格点模型(2DHP)提出了一种改进的蚁群算法(ACO)。受链生长型算法Pruned-Enriched Rosenbluth Method(PERM)的启发,在计算迹的时候增加了一个新的信息量,使得改进后的蚁群算法具有较快的收敛速度,同时采用基于极值动力学的优化方法(EO)进行局部搜索。求解基准实例的结果表明,该算法能够在保证解质量的前提下能大大缩短计算时间。
An improved ant colony optimization algorithm for the 2D HP protein folding is presented. Inspired by pruned-enriched rosenbluth method （PERM）, an additional pheromone is applied to direct ants’action. Furthermore, extremal optimization （EO） is used as a local search. We demonstrate that this improved ACO can be applied successfully to the protein folding problem. The results show that the algorithm can find these best solutions so far for the listed benchmarks. Within the achieved results, the search converged rapidly and efficiently.
出处
《计算机工程与设计》
CSCD
北大核心
2010年第8期1786-1788,1816,共4页
Computer Engineering and Design
基金
国家自然科学基金项目(60574063)
关键词
蛋白质折叠
格点模型
蚁群算法
极值优化
增长型算法
protein folding
HP model
ant colony optimization
extremal optimization
pruned-enriched rosenbluth method
