In this paper, we consider a Fuzzy Stochastic Linear Fractional Programming problem (FSLFP). In this problem, the coefficients and scalars in the objective function are the triangular fuzzy number and technological coefficients and the quantities on the right side of the constraints are fuzzy random variables with the specific distribution.Here we change an FSLFP problem to an equivalent deterministic Multi-objective Linear Fractional Programming (MOLFP) problem. Then by using Fuzzy Mathematical programming approach transformed MOLFP problem is reduced single objective Linear programming (LP) problem. A numerical example is presented to demonstrate the effectiveness of the proposed method.
KEYWORDSTrapezoidal fuzzy number; linear fractional programming problem; fuzzy Stochastic linear fractional programming problem; chance-constrained programming; fuzzy mathematical programming; multi-objective linear fractional programming problem CONTACT S. H. Nasseri nasseri@umz.ac.ir
In this paper, a fractional multi-commodity network flow problem with multi-choice parameters is studied under hybrid fuzzy-stochastic conditions. In this problem, coefficients of the objective function in both the nominator and denominator take the form of multi-choice parameters, with the alternative choices for the nominator and denominator of the fraction being represented by fuzzy-stochastic and fuzzy variables, respectively. The arc capacities are also considered as fuzzy-stochastic variables. The main goal of the present research is to provide the decision-maker with a model by the help of which he/she can manage unknown factors across a multi-commodity network. Given that this problem is herein investigated in a hybrid fuzzy-stochastic environment and includes multi-choice parameters, we use the probability-possibility approach, Lagrange interpolating polynomial, and the Charnes–Cooper variable transformation technique to convert the problem into a deterministic one. Finally, efficiency of the proposed model is evaluated by presenting a couple of numerical instances.
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