Optimal Allocation of Human Resource Structure Based on Capability Maturity Model Integration

In order to improve the economic benefits of enterprises and provide a scientific human resource management method for enterprises, an optimal allocation method of human resource structure based on the integration of capability maturity model is proposed. According to the capability maturity model and its maturity level, the capability maturity integration model is established, and the optimal allocation algorithm of human resources is designed according to the model principle. By constructing the personnel quality evaluation matrix and personnel allocation matrix, the human resource allocation model is established, and the cooperative game method is used to dynamically optimize the human resource allocation model. The experimental results show that this method effectively improves the economic benefits of enterprises, improves the efficiency of human resource allocation, and completes the preset goal.

Optimized Allocation of Resources for Intelligent Construction of Training Venues for Track and Field Teams

Because of the problems of low allocation efficiency and accuracy in the traditional resource allocation model for the intelligent construction of track and field team training venues, this paper proposes a new intelligent construction resource allocation model for track and field team training venues. A distributed data collection method is adopted to select the index data for the intelligent construction of the track and field team training venues to optimize the allocation of resources and the mined resource allocation index through extracting the optimized index characteristics. The goal of the optimization problem is transformed into a single-objective solving problem. The suggested approach is based on the two-level programming concept. The simulation experimental results show higher efficiency and better allocation effect of the proposed scheme compared to other state-of-the-art approaches. Our evaluation and observations suggest that the accuracy of the intelligent construction of track and field team training venues is between 90% and 99% which is higher than two other benchmarked models. Furthermore, the proposed model can quickly reach to an optimal decision.