Higher education resource optimal allocation and relationship with the biopharma and biotech industry

Abstract

Current educational resource allocation methods achieve resource allocation through a simple linear constraint approach to a single resource restriction, and the single resource allocation restriction causes the allocation results to easily fall into a local optimal solution, which not only has low allocation efficiency but also cannot allocate all the resources effectively, leading to the waste of educational resources of a certain category or several categories in pharma industries. To address the above problems, the algorithm of optimal allocation of higher education resources based on the relationship with the biopharma and biotech industry is proposed. In view of the above problems, an algorithm for optimizing the allocation of higher education resources biopharma and biotech industry is proposed. By establishing a multidimensional analysis model of educational resource data, the resource data are analyzed and processed to determine the factors affecting resource allocation. Combined with the actual establishment of the resource allocation optimization model, NSGA-II is used to solve the problem, and the optimal allocation scheme is obtained. The application of the proposed configuration algorithm to reduce the standard deviation of the resource discrepancy coefficient to 0.134 is demonstrated through simulation experiments, which can effectively reduce the discrepancy between resources.