Akademik Veri Yönetim Sistemi
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, cilt.11, sa.8, ss.1749-1780, 2020 (SCI-Expanded)
Supplier selection and evaluation is a crucial decision-making issue to establish an effective supply chain. Higher-order fuzzy decision-making methods have become powerful tools to support decision-makers in solving their problems effectively by reflecting uncertainty in calculations better than crisp sets in the last 3 decades. The q-rung orthopair fuzzy (q-ROF) sets which are the general form of both intuitionistic and Pythagorean fuzzy sets, have been recently introduced to provide decision-makers more freedom of expression than other fuzzy sets. In this paper, we introduce q-ROF TOPSIS and q-ROF ELECTRE as two separate methods and new approaches for group decision making to select the best supplier. As the existing distance measures in q-rung orthopair fuzzy environment have some drawbacks and generate counter-intuitive results, we propose a new distance measure along with its proofs to use in both q-ROF TOPSIS and q-ROF ELECTRE methods. Moreover, a comparison study is conducted to illustrate the superiority of the proposed distance measure. Subsequently, a comprehensive case study is performed with q-ROF TOPSIS and q-ROF ELECTRE methods separately to choose the best supplier for a construction company by rating the importance of criteria and alternatives under q-ROF environment. Finally, a comparison and parameter analysis are performed among the proposed q-ROF TOPSIS and q-ROF ELECTRE methods and existing q-ROF decision-making methods to demonstrate the effectiveness of our proposed methods.