Abstract
This article investigates multi-attribute group decision-making (MAGDM) problems based on interval-valued Pythagorean fuzzy linguistic sets (IVPFLSs). The IVPFLSs are regarded as an efficient tool to describe decision makers’ (DMs’) evaluation information from both quantitative and qualitative aspects. However, existing IVPFLSs based MAGDM methods are still insufficient and inadequate to deal with complicated practical situations. This article aims to propose a novel MAGDM method and the main contributions of the present work are three-fold. First, we propose new operations of interval-valued Pythagorean fuzzy linguistic numbers (IVPFLNs) based on linguistic scale function. Second, we propose new aggregation operators (AOs) of IVPFLNs based on power average operator and Muirhead mean. The proposed AOs take the interrelationship among any numbers of attributes into account and eliminate the bad influence of DMs’ unreasonable evaluation values on the final decision results. Third, based on the new operations and AOs of IVPFLNs, we introduce a novel approach to MAGDM and present its main steps. Finally, we discuss the effectiveness of the proposed approach and investigates their advantages through numerical examples.
Highlights
Multiple attribute group decision-making (MAGDM) theories and models have gained much attention and been extensively employed in practical decision-making problems, such as supplier selection [1], [2], investment selection [3], [4], smart medical device selection [5], signal processing [6] etc
We further propose some aggregation operators (AOs) of interval-valued Pythagorean fuzzy linguistic numbers (IVPFLNs) based on PMM, i.e. the IVPFL power Muirhead mean (IVPFLPMM) operator and the IVPFL power weighted Muirhead mean (IVPFLPWMM) operator
NEW OPERATIONS OF IVPFLNS BASED ON LINGUISTIC SCALE FUNCTIONS we aim to propose novel operations of IVPFLNs based on linguistic scale function (LSF)
Summary
Multiple attribute group decision-making (MAGDM) theories and models have gained much attention and been extensively employed in practical decision-making problems, such as supplier selection [1], [2], investment selection [3], [4], smart medical device selection [5], signal processing [6] etc. PFSs have been regarded as an efficient tool in portraying DMs’ complicated and fuzzy evaluation information in MAGDM process and quite a few novel decision-making methods have been proposed [9]–[14]. The MM is good at capturing the interrelationship among multiple attributes and this is the reason that it has been widely employed in information aggregation process [40]–[43] Recently, Li et al [44] integrated PA with MM and proposed the power Muirhead mean (PMM) operator, which takes the advantages of both PA and MM. We present a new MAGDM method based on the proposed AOs. In the new decision-making approach, the IVPFLPWA is employed to calculate the comprehensive decision matrix and the IVPFLPWMM is used to compute the overall evaluation values of alternatives.
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