The existing grey relational clustering method has limitations in the application of multidimensional sequences and cannot directly calculate the grey correlation degree between unequal-length sequences. In this paper, by introducing the multidimensional dynamic DTW distance into the existing 3D grey relational model, a new grey relational analysis model that can be applied to multidimensional data is proposed, which is based on DTW distance. The model does not require one-to-one correspondence of data points but evaluates the similarity of its geometric curves by calculating the shortest distance between sequences. In addition, since the traditional grey correlation clustering method is implemented, the method first extracts the reference sequence from the observation sequence and then calculates the similarity between the observation objects by calculating the grey correlation degree between each sequence and the reference sequence, so each object only needs to be calculated once. The experimental results show that the multidimensional grey correlation degree based on DTW distance and the grey relational clustering model oriented to multidimensional data are more accurate than other existing methods. Finally, the grey relation clustering method of multidimensional data is used to analyze the multiobjective human resource grey relational clustering model under time constraints, and the validity of the model is verified.