基于异构布谷鸟搜索算法的分子势能优化  

Heterogeneous Cuckoo Search Algorithm Based Molecular Potential Energy Optimization

作　　者：钱玉山 丁学明[1] QIAN Yushan;DING Xueming(School of Optimal-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《信息与控制》2020年第3期289-296,共8页Information and Control

基　　金：国家自然科学基金资助项目(11502145)。

摘　　要：分子最稳定构象的确立,可以被看作一个全局最优问题.分子结构决定了其性质和功能,在众多可能的分子构象中,最稳定的分子构象拥有最小的分子势能.然而,求解这个全局最小值是相当复杂的,而且计算上有一定难度,因为分子势能局部最小值的个数是随着分子大小呈指数增长的.因此,本文提出一种基于量子机制的、具有多样搜索策略的新型布谷鸟搜索算法(heterogeneous cuckoo search, HeCoS),并利用此算法优化简化的分子势能函数.结果表明HeCoS具有强大的全局最小值搜索能力、较快的收敛速度以及良好的鲁棒性,在性能上优于其他算法.The determination of the most stable conformers of a molecule can be regarded as a global optimization problem.The structure,characteristics,and behavior of a molecule are determined by molecular conformation.The most stable conformation is the global minimum of the molecular potential energy.However,in obtaining the global optimal value,the problem of finding the global minimum is highly complex and computationally difficult because of the number of local minima,which increases exponentially with the molecular size.A new variant of the cuckoo search algorithm with heterogeneous search strategies based on quantum mechanics,i.e.,heterogeneous cuckoo search(HeCoS)algorithm is presented.The proposed HeCoS algorithm is applied to optimize a simplified molecular potential energy function.The results show that the HeCoS algorithm has powerful capability for searching the global minimum,fast convergence speed,good robustness,and better performance than other algorithms.

关 键 词：全局优化 量子机制 分子势能函数 布谷鸟搜索算法 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TP181[自动化与计算机技术—控制科学与工程]