Optimization of Microeconomic Models Under Integrated Partial Differential Equations

Optimization Microeconomic Models Integrated Partial Differential Equations University Management.

Authors

  • Linwen Huo College of Finance and Economics, Yantai Institute of Science and Technology, Yantai, Shandong 265600,, China
  • Shumin Wei
    Puyan1922@outlook.com
    College of Finance and Economics, Yantai Institute of Science and Technology, Yantai, Shandong 265600,, China
  • Ianwei Wang Xinxiang Institute of Science and Technology, HeNan, Xin Xiang, 453003,, China

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Objectives: This study aims to optimize microeconomic models under integrated partial differential equations, focusing on microeconomics and mathematics. Specifically, it examines the optimization of a Microeconomic model in university management, considering the balance between teaching and research activities within departments. Methods/Analysis: The study employs integrated partial differential equations to model the behavior of individuals and firms in a market economy, coupled with microeconomic principles. It analyzes the competitive nature of teaching and research activities within a university department, accounting for resource allocation, suitability of materials, and the challenge of modifying departmental makeup in the short term. Novelty/Improvement: The novelty lies in integrating microeconomic modeling with mathematics, offering a comprehensive approach to university management optimization. By considering the competitive dynamics between teaching and research, as well as the constraints imposed by academic tenure and resource allocation, the model more closely reflects the reality of Higher Education institutions. Findings: The study demonstrates that the proposed model achieves an accuracy of 95% in optimizing resource allocation between teaching and research activities while maintaining quality and adhering to financial constraints. This finding underscores the effectiveness of integrating microeconomic principles with mathematical techniques in addressing complex management challenges within academic institutions.

 

Doi: 10.28991/HIJ-2024-05-04-09

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