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A cone crusher is a machine that crushes rock materials with high efficiency and low power consumption; it is one of the typical road construction equipment. To improve the production efficiency, mechanical performance, and crushing performance of the cone crusher, thus increasing profit, this study used Discrete element method (DEM) particle analysis software to optimize the structure of the moving cone, studied the crushing effect of the crusher, and carried out kinetics analyses. Based on DEM, the structure of the cone crusher cavity was analyzed and optimized. A Y51 cone crusher was selected as a representative example to study its moving cone structure. By analyzing the factors that affect the performance and efficiency of the crusher, the precession angle, base angle, shape, and rotational speed of the moving cone were optimized. Using the Genetic Algorithm-Support Vector machine method (GA-SVW), the optimal combination of parameters was determined, and the key parts of the crusher were thus optimized.