Abstract
Considering the characteristics such as fuzziness and greyness in real decision-making, the interval grey triangular fuzzy number is easy to express fuzzy and grey information simultaneously. And the partition Bonferroni mean (PBM) operator has the ability to calculate the interrelationship among the attributes. In this study, we combine the PBM operator into the interval grey triangular fuzzy numbers to increase the applicable scope of PBM operators. First of all, we introduced the definition, properties, expectation, and distance of the interval grey triangular fuzzy numbers, and then we proposed the interval grey triangular fuzzy numbers partitioned Bonferroni mean (IGTFPBM) and the interval grey triangular fuzzy numbers weighted partitioned Bonferroni mean (IGTFWPBM), the adjusting of parameters in the operator can bring symmetry effect to the evaluation results. After that, a novel method based on IGTFWPBM is developed for solving the grey fuzzy multiple attribute group decision-making (GFMAGDM) problems. Finally, we give an example to expound the practicability and superiority of this method.
Highlights
Multiple attribute group decision-making (MAGDM) is the process of comparing and choosing the best alternative by analyzing the evaluations of multiple attributes aggregated from decision-makers.And MAGDM problems have a wide application in real life, such as effect evaluation of environmental protection policies formulated by the government [1], the evaluation of international cooperation plans for energy development [2], the assessment of the comprehensive strength of different schools [3], the comparison of various schemes by enterprises in business negotiations [4], and the selection of enterprises’ purchasing schemes [5]
We find the ranking calculated by IGTFWPBM operator is consistent with methods [16,19,33], which illustrates the effectiveness of the grey fuzzy multiple attribute group decision-making (GFMAGDM) method based on the IGTFWPBM operator
In this study, considering the fuzziness and greyness in real decision-making, we developed a new method for solving GFMAGDM problems
Summary
Multiple attribute group decision-making (MAGDM) is the process of comparing and choosing the best alternative by analyzing the evaluations of multiple attributes aggregated from decision-makers. Jin and Liu [16] constructed the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method based on interval grey linguistic variables to solve the decision-making problem in a grey fuzzy environment. Tian et al [33] proposed the grey linguistic weighted Bonferroni mean operator to solve GFMADM problems which exit interrelationship between each attribute. The fuzzy part of the interval grey triangular fuzzy numbers is used to express the subjective evaluation of decision-makers on the attribute variables of alternatives, and the grey part is used to indicate the objective cognition degree of the decision-maker to the attribute variables of the alternatives. Compared with the existing form of expression of uncertain information, the interval grey triangular fuzzy numbers can reflect decision-makers’ subjective evaluation and objective cognition of evaluation objects, the decision-making information is more comprehensive.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
