Balanced Allocation of Educational Resources Based on Parallel Genetic Algorithm

Abstract

Higher education is one of the scarcest social resources, with high demand and low supply, and higher education is currently in limited supply in our country, making it difficult to resolve this contradiction. In addition to increasing investment in higher education as much as possible, the most important thing is to maximize the benefits of education through the rational allocation of resources. An evaluation index system of educational resource input-output was constructed, and a multiobjective function model of educational resource utilization efficiency and allocation efficiency was proposed. We should rationalize the allocation of resources and maximize the benefits of innovation and entrepreneurship education in colleges and universities. By combining particle swarm optimization with genetic algorithm, we can simulate and solve the model. The simulation results suggest that by optimizing the usage and allocation efficiency of innovation, it may be increased. College and university entrepreneurship education resources have increased by 18.72 percent and 20.98 percent, respectively, on average, and tend to be in a balanced state, which can realize the optimization of education resources allocation.