A New Approach to Solve Fuzzy Linear Fractional Programming Problems via Rank Function of Trapezoidal Fuzzy Numbers

Abstract

Ranking fuzzy numbers is essential to descriptive decision-making and several other fuzzy systems and applications. Numerous techniques have been put forth to rank fuzzy numbers. It has been demonstrated that each of these approaches occasionally yields findings that are counterintuitive. The aim of this studies can be factors such as: firstly, Willingness to improve manufacturing production. Secondly, to minimize production time (negated iteration). Finally, the aspiration to discover new linear fuzzy script The study of “Fuzzy Linear Fractional Programming” FLFP problems with “trapezoidal fuzzy numbers” has been addressed in this research, where the constraints are actual numbers and the objective functions are fuzzy numbers. Obtaining the fuzzy optimum solution with unconstrained variables and parameters has been made possible in this study by the introduction of a modern, effective strategy for the FLFP problems. The newly employed transformation methodology is similarly based on the suggested method of crisp linear fractional programming foundation. To get an ideal answer, a computational method has been provided. A real-world example has been given to show the effectiveness of our suggested methodology.