Abstract: With the increasing demand for refined design of ship structures, the dimensions of design variables for ship structure optimization problems have significantly increased, reaching hundreds or thousands. Structural finite element simulation analysis has also become more detailed and time-consuming, and structural optimization design problems have further become time-consuming high dimensional optimization problems. In recent years, studying efficient methods for solving high dimensional optimization problems and developing high dimensional optimization design techniques for ship structures have become important research hotspots and mainstream development trends. This paper systematically summarizes recent research progress in high dimensional optimization methods and their applications in ship structural optimization. First, the connotation of high dimensional optimization problems is described, and solution methods based on collaborative/decomposition optimization frameworks and the key technologies involved are outlined in detail. Subsequently, a comprehensive explanation of solution methods is provided from two major directions: high dimensional constrained optimization problems and high dimensional expensive optimization problems. Afterwards, domain knowledge in ship structural optimization design and its recent engineering applications are summarized. Finally, the main issues and challenges in the field of high dimensional optimization design for ship structures are pointed out, and prospects for future research directions of ship structural high dimensional optimization are outlined from three perspectives: surrogate model techniques, multitask optimization design techniques, and optimization design techniques empowered by artificial intelligence.