
This paper presents a quadratically constrained multiobjective quadratic fractional programming model (MOQFPM) and proposed a methodology to obtain a best preferred solution with the help of parametric functions and using fuzzy goal programming. In the initial stage, we obtain a non-fractional optimization model from the multi-objective quadratic fractional programming model by assigning a vector of parameters to fractional functions. Then, in the next stage, we use fuzzy goal programming approach to obtain the best preferred solution for the decision maker to the optimization problem by finding membership functions and aspiration levels of each objective function. This methodology proposes an efficient method to obtain Pareto-optimal solution of MOQFPM.
fuzzy goal programming, parametric approach, Fuzzy and other nonstochastic uncertainty mathematical programming, Quadratic programming, vector of parameters, Fractional programming, multiobjective quadratic fractional programming model, membership functions, Multi-objective and goal programming, fuzzy goals
fuzzy goal programming, parametric approach, Fuzzy and other nonstochastic uncertainty mathematical programming, Quadratic programming, vector of parameters, Fractional programming, multiobjective quadratic fractional programming model, membership functions, Multi-objective and goal programming, fuzzy goals
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