ENLPM مدل برنامه ريزي رياضي غيرخطي بسط داده شده جهت تخمين پارامترهاي تابع توليد و بهينه سازي به طور همزمان

An Extended Nonlinear Mathematical Programming Model (ENLPM) for Linear Least Squares Estimations and Optimal Decision - Makings, Simultaneously

The extended mathematical programming model (EMPM) is presented here as a new tool to study both regression (for Linear Least Squares Estimation) rule and optimal decision-making problems simultaneously, using an experimental wheat production data. First, the essentials of the new technique presented in this paper are outlined for the estimation of the coefficients of a polynomial (quadratic) biological production function, for linear least square estimation (linear in parameters), as compared with the Ordinary Least Square (OLS) rule. Secondly, both the estimation of the parameters of the experimental biological production function and related optimal decision making are done using the extended quadratic programming model (ENLPM), by combining the estimated parameters and economic data, simultaneously. Thirdly, the estimated production parameters along with product and input prices are used to examine several economic characteristics by generating the data for underlying variable cost Function, supply Function, Input Demand Function, Marginal Cost Function (MC), Optimal Input combinations, optimal physical and economic level of production for different output as well as input prices. The results show that through, ENLPM one is able to generate not only the exact final results of O1,S for parameter estimation under any kind of imposed restrictions, but also for least - cost input combinations and other related optimal decision makings, simultaneously.