  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.
