A Mathematical Budgeting Model in the Public Sector - Robust Optimization Approach

Nowadays most of resource allocation is mental, empirical and based on the old methods. So it does not take general satisfaction and does not have generalization ability and mathematical confirm, Hence using from quantity theory for nearing of quantitative and qualitative human resource is essential objective. Budgeting lows based on forecasting which always face with errors and uncertainty. These errors are Prediction errors, Measurement Errors, Implementation Errors, so mirror change in forecasting amount, Measurement and Implementation cause to hesitation on optimally and feasibility for budgeting lows. Goal of this article is designing of a budgeting model in the public sector to be able for glancing uncertainty factor which with preserving optimally and feasibility allocation area in the budget low in contorting with changing, guaranty his flexibility in the also implementation. There are different approaches for glancing of effect of uncertainty which from these approaches, we selected robust optimization approach. And this mathematical budgeting model developed by using of Soyster robust model, Ben-Tal & Nemirovski model and Bertsimas & Sym model. Until on foundation of measurement convex, decision makers from situation of now and future of country, be able use from every one these robust models.