This research paper delves into the domain of Linear Fractional Programming (LFPP) with a specific focus on sensitivity analysis. Sensitivity analysis plays a crucial role in understanding the impact of changes in parameters or data values on the optimal solution of LFPP. The paper introduces the concept of adding a new constraint to an existing LFPP model and explores its implications on the optimal solution. Through rigorous methodology, the study investigates scenarios where the newly added constraint either preserves the optimality of the existing solution or leads to structural variations. The findings contribute to a deeper understanding of LFPP and offer insights into effectively incorporating new constraints to address evolving requirements.

Keywords: Linear Fractional Programming, Sensitivity Analysis, Optimization, Constraints, Structural Variations.