Comparing three modeling approaches of Fuzzy, Robust and Robust Fuzzy in Performance-Based Budgeting

The purpose of this study is primarily to provide a performance-based budgeting model (PBB) in the Institute for Management and Planning Studies (IMPS). So the one hand allocating budgets to programs is based on programs’ importance and on the other hand, allocating budgets to groups is based on per capita students that were assigned by Ministry of Sciences, Researches and Technology. Considering various criteria in this institute, the PPB Goal programming model is designed. An important point in designing the PBB model is the use of efficiency coefficient calculated based on the Data Envelopment Analysis (DEA) to determine important coefficient of each educational group for budget allocation. In addition, importance coefficient of each program and the goals of the problem are determined based on paired comparison by experts. Given the uncertainty in the parameters of the PBB model, using robust and fuzzy logic, some adopted scenarios from nominal model are designed including robust, fuzzy, and fuzzy-robust models. Finally, the obtained solutions from these models are compared and the strengths and weaknesses of each of them are examined. In addition, in order to evaluate the effectiveness and efficiency of the proposed models, Monte Carlo simulation is used. The modeling results and simulations provide useful information to decision makers for making a reasonable decision by balancing the decision risk levels (possibility of violating constraints) and conservation level.