The intelligent equipment manufacturing cycle is long, resource consumption is large, in the manufacturing process often needs for different production stages to take multiple batches of resource procurement strategy and resource optimization configuration. Based on this situation, this paper proposes an intelligent equipment procurement strategy and resource optimization design. The problem description is established, the variables and constraints are introduced, and the construction of the objective optimization model is completed. The corresponding optimization model is solved using the improved Gray Wolf algorithm and the improved differential evolution algorithm. After the training and optimization of the improved gray wolf algorithm, the total cost of intelligent equipment procurement is 180150 yuan, and the procurement strategy is to select the preferred supplier at the corresponding point in time, according to which the procurement strategy can be a realistic intelligent equipment procurement task. In addition, the average deviation of resource optimization allocation based on the improved differential algorithm is only 0.35%, which is better than the performance of the traditional differential algorithm and genetic algorithm, confirming the feasibility of this paper’s algorithm in intelligent equipment resource allocation optimization model aiming at cost optimization.