M-OPARA: A Modified Approach to the OPARA Method

Do Duc Trung; Nazlı Ersoy; Tran Van Dua; Duong Van Duc; Manh Thi Diep

doi:10.31181/dmame8120251334

Authors

Do Duc Trung Hanoi University of Industry, Cau Dien, Bac Tu Liem, Hanoi, Vietnam https://orcid.org/0000-0002-0059-2603
Nazlı Ersoy Osmaniye Korkut Ata University, Osmaniye, 80000, Türkiye https://orcid.org/0000-0002-0059-2603
Tran Van Dua Hanoi University of Industry, Cau Dien, Bac Tu Liem, Hanoi, Vietnam https://orcid.org/0000-0002-0059-2603
Duong Van Duc Hanoi University of Industry, Cau Dien, Bac Tu Liem, Hanoi, Vietnam https://orcid.org/0000-0002-0059-2603
Manh Thi Diep Hanoi University of Industry, Cau Dien, Bac Tu Liem, Hanoi, Vietnam https://orcid.org/0000-0002-0059-2603

DOI:

https://doi.org/10.31181/dmame8120251334

Keywords:

Multi-criteria decision-making; MCDM; OPARA method; M-OPARA method

Abstract

The process of selecting the optimal option among multiple conflicting criteria is a fundamental task across various disciplines and is known as multi-criteria decision-making (MCDM). This study seeks to enhance the Objective Pairwise Adjusted Ratio Analysis (OPARA) method, which is limited by its inability to rank alternatives when any criterion within the decision matrix assumes a zero value. To address this limitation, an additional transformation step is introduced, resulting in the development of the M-OPARA method. The effectiveness of the M-OPARA method has been rigorously assessed through diverse case studies, incorporating different sets of criterion weights derived from 20 scenarios, and by comparing its performance against several MCDM techniques, including OPARA, PIV, ROV, SAW, WASPAS, MARCOS, and FUCA. The findings indicate that the M-OPARA method achieves high accuracy in ranking alternatives and successfully mitigates the constraints of the OPARA method. The methodological advancements introduced by M-OPARA constitute a substantial improvement in the rank ability of alternatives within decision-making frameworks. This novel approach facilitates more precise and dependable decision-making in practice, equipping decision-makers with a more flexible and robust analytical tool

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