Efficient Fuzzy Solutions for Linear Fractional Programming Problems: Using Pentagonal Fuzzy Numbers and the Decomposition Method

Authors

DOI:

https://doi.org/10.24237/04.02.755

Keywords:

Linear Fractional Programming Problems, Fully Fuzzy Linear Fractional Programming Problems, Fuzzy Sets, Pentagonal Fuzzy Numbers, Decomposition Method

Abstract

This paper presents an efficient method for solving fully fuzzy linear fractional programming (FFLFP) problems using pentagonal fuzzy numbers (PFNs) and the decomposition method. In real-world decision-making, uncertainty is inevitable, and fuzzy set theory provides a powerful framework to model such uncertainty. The proposed approach decomposes the FFLFP problem into five independent linear fractional programming (LFP) problems. Each LFP is transformed into a linear programming (LP) problem using the Charnes and Cooper transformation and solved via the simplex method. The obtained solutions are then aggregated to construct an efficient fuzzy solution. A numerical example is provided to demonstrate the effectiveness and applicability of the method. The results show that the proposed technique is accurate and suitable for solving complex optimization problems under uncertainty.

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Author Biography

  • Maher Nawkhass, Mathematics Department, College of Education, Salahaddin University-Erbil, Erbil, Kurdistan Region, Iraq

    Dr. Maher Ali Nawkhass is a lecturer in the Mathematics Department at Salahaddin University in Erbil, Iraq. He holds a Ph.D. in Optimization – Applied Mathematics, focusing on solving complex mathematical problems across various fields. His research interests lie in the realm of fractional programming, where he develops innovative approaches to tackle multi-objective problems and optimize solutions.

    Dr. Nawkhass is an experienced educator with a diverse teaching background, encompassing calculus, numerical analysis, and computer skills. His work has been recognized through publications in international journals like the International Journal of Nonlinear Analysis and Applications and the International Journal of Fuzzy System Applications. He is dedicated to fostering a deeper understanding of mathematics and its applications within the academic community.

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Published

2026-04-30

How to Cite

Mustafa, R., & Nawkhass, M. (2026). Efficient Fuzzy Solutions for Linear Fractional Programming Problems: Using Pentagonal Fuzzy Numbers and the Decomposition Method. ASJ - Academic Science Journal, 4(2), 51-57. https://doi.org/10.24237/04.02.755

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