TY - JOUR ID - TI - An Application Model for Linear Programming with an Evolutionary Ranking Function AU - Rasha Jalal Mitlif PY - 2022 VL - 35 IS - 3 SP - 146 EP - 154 JO - Ibn Al-Haitham Journal For Pure and Applied Sciences مجلة ابن الهيثم للعلوم الصرفة والتطبيقية SN - 16094042 25213407 AB - One of the most important methodologies in operations research (OR) is the linear programming problem (LPP). Many real-world problems can be turned into linear programming models (LPM), making this model an essential tool for today's financial, hotel, and industrial applications, among others. Fuzzy linear programming (FLP) issues are important in fuzzy modeling because they can express uncertainty in the real world. There are several ways to tackle fuzzy linear programming problems now available. An efficient method for FLP has been proposed in this research to find the best answer. This method is simple in structure and is based on crisp linear programming. To solve the fuzzy linear programming problem (FLPP), a new ranking function (RF) with the trapezoidal fuzzy number (TFN) is devised in this study. The fuzzy quantities are de-fuzzified by applying the proposed ranking function (RF) transformation to crisp value linear programming problems (LPP) in the objective function (OF). Then the simplex method (SM) is used to determine the best solution (BS). To demonstrate our findings, we provide a numerical example (NE).

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