Abstract: With the increasing demand for refined design of ship structures, the dimensionality of design variables in ship structural optimization problems has significantly increased, reaching hundreds or even thousands. Meanwhile, finite element-based structural simulation analyses have become more detailed and computationally expensive, further transforming structural optimization design into time-consuming high-dimensional optimization problems. In recent years, the development of efficient solution methods for high-dimensional optimization problems and corresponding design techniques for ship structures has become a major research hotspot and a mainstream development trend. This paper systematically reviews recent research progress in high-dimensional optimization methods and their applications in ship structural optimization. First, the concept and characteristics of high-dimensional optimization problems are introduced, and solution methods based on cooperative and decomposition optimization strategies, together with key enabling technologies, are discussed in detail. Subsequently, representative solution methods are elaborated from two major perspectives: high-dimensional constrained optimization problems and high-dimensional expensive optimization problems. In addition, domain knowledge in ship structural optimization design and its recent engineering applications are summarized. Finally, the main issues and challenges in high-dimensional ship structural optimization are identified, and future research directions are outlined from three perspectives: surrogate modeling techniques, multitask optimization design techniques, and artificial intelligence-empowered optimization strategies.