Research Article
Human Resource Scheduling Control Method Based on Deep Reinforcement Learning
@INPROCEEDINGS{10.1007/978-3-031-18123-8_28, author={Shaoping Zhang and Bo Sun}, title={Human Resource Scheduling Control Method Based on Deep Reinforcement Learning}, proceedings={Multimedia Technology and Enhanced Learning. 4th EAI International Conference, ICMTEL 2022, Virtual Event, April 15-16, 2022, Proceedings}, proceedings_a={ICMTEL}, year={2022}, month={10}, keywords={Deep reinforcement learning Human resources Dispatching control}, doi={10.1007/978-3-031-18123-8_28} }- Shaoping Zhang
Bo Sun
Year: 2022
Human Resource Scheduling Control Method Based on Deep Reinforcement Learning
ICMTEL
Springer
DOI: 10.1007/978-3-031-18123-8_28
Abstract
With the increasing importance of human resource management in project process management, human resource scheduling and control methods also need to keep pace with the times. Continuing to use the traditional human resource scheduling control method will waste a lot of potential value of human resources. Therefore, a human resource scheduling control method based on deep reinforcement learning is proposed. By constructing the human resource scheduling control model, the minimum human cost expenditure under various constraints is obtained; Design the deep reinforcement learning algorithm, and design the scheduling algorithm for specific scheduling objectives for the human resources scheduling control center; Create a model-based human resource scheduling management and control evaluation system, and improve the relationship between the comprehensive evaluation value and the advantages and disadvantages of multi project human resource scheduling. Experiments show that this human resource scheduling control method can guide different problems to allocate goals. Considering the time factor, the optimal solution of human resource scheduling and control can be obtained.
