A novel computational method for neutrosophic uncertainty related quadratic fractional programming problems

Abstract

This study introduces a novel method for addressing the pentagonal quadratic fractional
programming problem (PQFPP). We employ pentagonal neutrosophic numbers for the objective function's cost,
resources, and technological coefficients. The paper transforms the PQFPP into a standard quadratic fractional
programming (QFP) problem via the score function. By leveraging the Taylor series approach, the modified
QFP is simplified to a single-objective linear programming (LP) task, amenable to resolution through
conventional LP algorithms or software tools. A numerical example serves to demonstrate the efficacy of the
suggested approach. Moreover, comparative analyses and benefits reveal that the newly developed techniques
outperform existing solutions in current scholarly works.