2019/10/13 by Bing Yu, Yu Bing, Lei Zhang +2
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · Mathematics · Physics and Astronomy · #Advanced Chemical Physics Studies #FOS: Mathematics #Machine Learning in Materials Science #Numerical Analysis (math.NA) #Protein Structure and Dynamics #cs.NA #math.NA
paper · pdf · doi:10.48550/arxiv.1910.05703
arxiv created 2019/10/13 · openalex publication_date 2019/10/13 · arxiv updated 2019/10/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Searching saddle points on the potential energy surface is a challenging problem in the rare event. When there exist multiple saddle points, sampling different initial guesses are needed in most dimer-type methods in order to find distinct saddle points. In this paper, we present a novel global optimization-based dimer method (GOD) to efficiently search saddle points by coupling ant colony optimization (ACO) algorithm with optimization-based shrinking dimer (OSD) method. In particular, we apply OSD method as a local search algorithm for saddle points and construct a pheromone function in ACO to update the global population. By applying a two-dimensional example and a benchmark problem of seven-atom island on the (111) surface of an FCC crystal, we demonstrate that GOD shows a significant improvement in computational efficiency compared with OSD method. Our algorithm offers a new framework to open up possibilities of adopting other global optimization methods to search saddle points.