This paper presents an optimization design method for heliostat fields by combining physical modeling with intelligent optimization. A generalized mirror surface diagram is derived using the cone-ray model, and optical efficiency and shadow-blocking areas are calculated via the micro-element integration method and quadrat counting principle. A Particle Swarm Optimization (PSO) algorithm is constructed, treating each heliostat as a particle and guiding the search in a two-dimensional distribution space based on historical best fitness values. To enhance the model’s flexibility, three additional parameters—length, width, and installation height—are introduced, expanding the solution space to five dimensions. The improved PSO model enables dynamic global optimization of both positional and dimensional parameters, resulting in a heliostat field layout that meets the required power output with higher overall efficiency.