Taylor series linearization for fully fuzzy multi-objective fractional programming in educational systems

Anitha Ganesan (SRM Institute of Science and Technology)
Ganesan Kandasamy (SRM Institute of Science and Technology)

Bulletin of Electrical Engineering and Informatics
Vol 15, No 2: April 2026

This study examines the fully fuzzy multi-objective linear fractional programming problem (FFMOLFPP), whereby both the objective functions and restrictions incorporate fuzzy parameters represented as triangular fuzzy numbers (TFN), without converting them into crisp values. A hybrid solution approach is presented to tackle the intrinsic nonlinearity and uncertainty. Initially, the imprecise numbers are transformed into parametric representations via the y- cut method. A first-order Taylor series expansion is subsequently utilized to linearize each fractional objective function around a fuzzy decision point. The linearized objectives are then consolidated by the weighted sum approach, transforming the multi-objective fuzzy model into a single-objective linear program. Numerical examples validate the strategy and demonstrate the improved accuracy and efficiency of the proposed methodology.