Heuristic Optimization Of Natural Production Inventory Models With The Preference Of A Decision Maker

In this paper, two natural production inventory models based on fuzzy total production inventory cost with the preference of a decision maker are introduced, and combined by natural number parameters in which values are linguistic values in natural language, crisp real number variables, and fuzzy number variables. These are the one natural production inventory model for crisp production quantity, and the other natural production inventory model for fuzzy production quantity. The natural arithmetical operations of both natural numbers and fuzzy numbers by Function Principle are used to compute fuzzy total production inventory cost of each natural production inventory model. Graded k-preference integration representation method is discussed for defuzzifying fuzzy total production inventory cost by preference of decision maker. Furthermore, Extension of the Lagrangean method is used to solve inequality constrain problem in our natural production inventory model. We find out that our optimal solutions can be specified to the classical production inventory model when preference 0.5 of decision maker and natural numbers and fuzzy numbers in our models are crisp real numbers.