Taylor Series Approach for Solving Multi-level Large Scale Fractional Programming Problem with Stochastic Parameters in Constraints

Abstract

This paper presents a solution algorithm to solve a multi-level large scale fractional programming problem with individual chance constraints (CH-MLLSFP). We assume that there is randomness in the right-hand side of the constraints only and that the random variables are normally distributed. The basic idea in treating (CH-MLLSFP) is to convert the probabilistic nature of this problem into a deterministic multi-level large scale fractional programming problem (MLLSFPP). A solution of multi-level large scale fractional programming problem is presented using aTaylor series to avoid the complexity of fractional nature. An illustrative example is discussed to demonstrate the correctness of the proposed solution method.