Multiobjective linear fractional programming model with equality and inequality constraints under pentagonal intuitionistic fuzzy environment

Multi-objective Linear Fractional optimization simultaneously addresses diverse goals using fractional programming techniques, offering a versatile decision-making framework adaptable to complex problems. The integration of Multiobjective Linear Fractional principles within an Intuitionistic Fuzzy Environment reshapes decision-making, optimizing multiple objectives concurrently amid imprecise information. This innovative fusion of linear fractional programming and intuitive, fuzzy logic forms a flexible framework to efficiently address complex problems, accounting for uncertainties and diverse decision criteria, expanding the solution spectrum comprehensively. In this research paper, the multi-objective optimization issue is modelled in a fuzzy intuitionistic environment. The cost of objective function, decision making variable and coefficients are to be pentagonal intuitionistic fuzzy number (PIFN). Furthermore in this paper we take up a problem where the constraints are both equality and inequality and the crisp version is achieved using novel fractional to linear transformation with aid of the accuracy function defuzzified the constraints where the uncertain parameters are represented as intuitionistic pentagonal fuzzy numbers. We have constructed alternate approach a to resolve multi-objective optimization problems. The suggested approach entails thinking objectively when making decisions. For the simultaneous optimal evaluation of each objective. The transformation which converted the IFMOLFPP into crisp multiobjective linear programming problem(CMOLPP) by proposed strategy. Where the converted CMOLPP was solved by using lingprog to get optimal solution for CMOLPP. The numerical examples are provided to demonstrate the effectiveness of the suggested solution technique. To show the practical applicability, a case study of airline issue is also examined.