Multi Skill Human Resource Group Intelligent Scheduling Method Based on Reinforcement Learning

To improve the intelligence of multiskilled human resource group scheduling, a multiskilled human resource group intelligent scheduling method based on reinforcement learning is proposed. It is divided into six steps to build an enterprise project group, mainly including the definition of the project group, project selection and evaluation and resource allocation of the project group. The focus is on the research and establishment of a project group selection evaluation model and resource allocation model. At the same time, during the implementation of the project group, the structure and plan of the project group are constantly adjusted through feedback information to improve the efficiency of multiple project implementation. Based on reinforcement learning, the scheduling direction of the multiskilled human resources group is determined. The selected reinforcement learning algorithm is the Q reinforcement learning method, that is, an offline instantaneous TDOA algorithm independent of the environmental model. A Kubernetes group intelligent scheduling model is constructed, and a simulated annealing genetic algorithm is designed to solve the group intelligent scheduling model to realize the group intelligent scheduling of multiskilled human resources. The test results show that the scheduling failure rate of this method is low in the cluster environment with sufficient and insufficient resources, indicating that this method has broad application prospects.