Providing a Framework for Allocating Public R&D Budget to the Universities Using Robust Optimization

Government-funded universities play a central role in national research and development (R&D). However, due to the government's budget constraints, the optimal allocation of public resources has become very important. In this study, a decision support framework was developed for the optimal and robust allocation of the R&D budget to maximize the direct and uncertain outputs of R&D activities in universities. The experiments were designed in two phases. In the first phase, without considering the uncertainty of R&D outputs of universities, the optimal budget allocation was determined according to three scenarios for each university. By changing the model parameters (robustness cost control parameter and output uncertainty control parameter), the optimal budget allocation plan in uncertain and robust conditions was calculated for 12 scenarios. The analysis of data using descriptive statistics methods and the comparison of results showed that in the current situation, there was no clear correlation between R&D outputs and the R&D budget allocated to the universities, and the budget allocation process was very volatile and lacked a clear increasing or decreasing pattern. While the R&D budget that was calculated in a robust optimal way showed a logical and proportional trend to the R&D activities’ output. Also, the optimal model distributed the total available budget for the universities in such a way as to achieve the maximum performance in the total budget ceiling. Implementing the model for 5 universities in 6 consecutive years improved the output from a minimum of 2 to a maximum of 6% and saved the allocated budget from 0.1 to 1.1%.