This paper presents a new modified technique for order preference by similarity
to ideal solution (M-TOPSIS) approach for unraveling stochastic fuzzy multi-level
multi-objective fractional decision making problem (ML-MOFDM) problem. In the
proposed model the coefficients and the scalars of the fractional objectives have a
fuzzy nature. The right-hand sides are stochastic parameters also, both of the lefthand
side coefficients and the tolerance measures are fuzzy kind. In this manner, the
deterministic-crisp ML-MOFDM model of stochastic fuzzy ML-MOFDM can be
gotten utilizing chance constrained strategy with predominance plausibility criteria
and the -cut methodology. In literature, almost all works on multi-level fractional
programming are the crisp version, in which they convert the fractional functions
into a linear one using a first order Taylor series which causes rounding off error.
The proposed M-TOPSIS approach presents a new method for solving such problem
without approximating or changing the nature of the problem. An algorithm to clear
up the M-TOPSIS approach, just as illustrative numerical model is displayed.