Considering the practical needs of equipment utilization, emergency equipment preparedness, and improving the efficiency of equipment maintenance, the relationship between equipment utilization and maintenance was analyzed, an optimized method for equipment utilization based on preventive maintenance theory was proposed, and a multi-objective optimization model aimed at maximizing equipment presence rate, equipment motor-hour reserve compliance rate, equipment availability rate, and minimizing equipment maintenance costs was established, with the constraint of balancing the revenue and expenditure of motor hours. Given the high-dimensional and large-scale difference characteristics of the established model’s objectives, an improved NSGA-III algorithm was designed for solving. The crossover and mutation evolutionary operations based on DNA, enhances the evolutionary efficiency of the population, and the improved adaptive normalization method enhances population diversity and algorithm convergence speed. Taking the annual equipment utilization optimization as an example, the improved NSGA-III algorithm was compared with the traditional NSGA-III algorithm. The experimental results verified the feasibility and efficiency of the proposed model and algorithm in solving this problem. By analyzing the trend of objective function values for a large number of equipment utilization plans and the detailed indicators of plans that achieve extreme values for single objectives, different preference-based equipment utilization optimization plans were proposed, which can provide a reference for the optimization of equipment use in the military.