Evaluation of sustainable third-party reverse logistics providers using a Fermatean fuzzy rough number-based decision-making framework

نویسندگان

1 Institute of Mathematics, University of the Punjab, New Campus, Lahore 4590, Pakistan

2 Institute of Mathematics, University of the Punjab, New Campus, Lahore 4590, Pakistan

doi
10.22111/ijfs.2025.9260
چکیده

Evaluating third-party reverse logistics providers (3PRLPs) is a complex task, often challenged by cognitive biases andincomplete, uncertain data in group decision-making contexts. To overcome these challenges, this study proposes anovel decision-support framework that integrates Fermatean fuzzy rough numbers with an extended entropy weightmethod and a new ranking technique. Fermatean fuzzy rough numbers effectively capture uncertainty and subjectivitywithout relying on predefined parameters, addressing key limitations in provider evaluation. The extended entropyweight method objectively determines the importance of decision criteria across economic, environmental, social, andrisk dimensions. The framework enhances decision accuracy by integrating three ranking techniques into an aggregatedindex, minimizing information loss while accommodating expert preferences. A case study on sustainable 3PRLPevaluation in the Malaysian food industry demonstrates the model’s practicality, while sensitivity and comparativeanalyses validate its robustness and superiority over existing approaches.