Goal programming approach to linear fractional bilevel programming problem based on Taylor series approximation

This paper deals with linear fractional bilevel programming problem. The goals of objective functions are determined by optimizing individual objective function subject to the system constraints. Then the fractional objective functions are transformed into equivalent linear functions at the optimal solution point by using first order Taylor polynomial series. Since the objectives of the decision makers are potentially conflicting in nature, decision makers consider relaxation on decision for avoiding decision deadlock. To demonstrate the efficiency of the proposed approach, a numerical example is solved and compared with other approaches.