Optimization of University Scientific Research Project Management Resources Based on Genetic Algorithm

Abstract

This article aims to solve the problem of resource optimization in the management of scientific research projects in universities, and proposes a resource optimization model based on Genetic algorithm (GA). By collecting and processing real data and conducting simulation experiments, this article evaluates the performance and stability of the model. The experimental results show that GA has good convergence and solution quality in resource optimization. Compared with other methods, GA has advantages in optimization effect and stability. It can maintain good performance under different data sets and parameter settings, and its stability is basically around 89.5%. The stability test further verified the reliability of the model in different scenarios. Therefore, this article holds that GA has application potential in the optimization of scientific research project management resources in universities, which can provide effective decision support for managers and realize rational allocation and efficient utilization of resources. These results provide an important reference for future research, and can promote the development of scientific research project management in universities in a more intelligent and optimized direction.