An Innovative Approach for Solving Fully Triangular Q- Rung Orthopair Fuzzy Linear Fractional Optimization Problem

Sultan S. Alodhaibi; Moodi Abdulrahman Abdullah Al- Rajeh; Hamiden Abd El-Wahed Khalifa

doi:10.31181/msa41202741

Authors

Sultan S. Alodhaibi Department of Mathematics, College of Science, Qassim University, Buraydah, Saudi Arabia Author https://orcid.org/0000-0002-0064-1110
Moodi Abdulrahman Abdullah Al- Rajeh Department of Mathematics, College of Science, Qassim University, Buraydah, Saudi Arabia Author https://orcid.org/0009-0002-1325-0060
Hamiden Abd El-Wahed Khalifa Department of Operations and Management Research, Faculty of Graduate Studies and Statistical Research, Cairo University, Giza, Egypt Author https://orcid.org/0000-0002-8269-8822

DOI:

https://doi.org/10.31181/msa41202741

Keywords:

Linear Fractional Programming, Fourier- Motzkin Elimination Method, Triangular Q- Rung Orthopair Numbers, Optimal Solution

Abstract

This paper addresses a nonlinear linear fractional programming (NLFP) problem characterized by parameter uncertainty. To effectively capture imprecision in the model, all coefficients in both the objective function and the constraints are represented using triangular q-rung orthopair fuzzy (q-ROF) numbers (q-ROFNs). The fuzzy formulation is then transformed into an equivalent crisp linear fractional programming model through the application of an appropriate score function. To solve the resulting deterministic model, a novel procedure based on the Fourier–Motzkin elimination technique is developed. The proposed method employs boundary analysis and provides a straightforward and computationally efficient alternative to classical approaches, such as the two-phase simplex method. Finally, a numerical example is included to illustrate the effectiveness and implementation steps of the proposed solution methodology, followed by concluding remarks.

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Author Biographies

Sultan S. Alodhaibi, Department of Mathematics, College of Science, Qassim University, Buraydah, Saudi Arabia

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Hamiden Abd El-Wahed Khalifa, Department of Operations and Management Research, Faculty of Graduate Studies and Statistical Research, Cairo University, Giza, Egypt

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