This paper proposes an approach where it can be applied to the optimization decision making problems under various uncertainties and solves a multi-level fractional programming problem (MLFPP) involving stochastic parameters coefficient in which some dependent variables are to be constrained with a predefined probability. Such problems are called optimization under chance constraints. In this work, the first phase of the solution approach, we convert the probabilistic nature (stochastic) of this problem in the constraints into a multi-level fractional programming problem (MLFPP). Then the second phase, we use the 1Storder Taylor series polynomial series to convert (MLFPP) into a multi-level linear programming problem (MLFPP) for generating a compromise solution for this problem. In addition, a numerical example is provided to demonstrate the correctness of the proposed solution.

Full text: IJEIR_1098_Final.pdf