Fast beam migration (FBM), characterized by its super-high efficiency in velocity model building, consists of three main steps: beam forming, beam propagation, and image forming. The super-high efficiency is achieved by beam forming, as it needs only to be performed once for one dataset and is independent of velocity, and the other two steps take relatively little time. However, compared to the beam-propagation and image-forming steps, the beam-forming step is still quite time-consuming owing to the high-dimensional computing problem of estimating the source and receiver slope orientation of a beam. Furthermore, previous methods for estimating the source and receiver slope orientation of a beam struggled to deal with intersecting events, leading to poor imaging results for complex subsurface structures, such as unconformities or faults, where events often intersect. We propose the use of a three-step multimodal optimization method based on the neighborhood crowding differential evolution (NCDE) algorithm to estimate the source and receiver slope orientation of a beam during the beam-forming step, which can quickly and accurately obtain slope orientations when events intersect. We first test the three-step multimodal optimization algorithm on a 3D super-gather and provide the parameter criteria. We then apply the FBM based on the three-step multimodal optimization algorithm to the Marmousi 2 and 3D SEG/EAGE salt models. Both results demonstrate that the proposed method can image intersecting events well and that the imaging quality of complex zones is improved. We also apply the proposed method to a 2D offshore seismic dataset containing abundant intersecting events, which validates the practicality of the proposed method.