Interval-valued spherical fuzzy MABAC method based on Dombi aggregation operators with unknown attribute weights to select plastic waste management process - Mandal, Utpal; Seikh, Mijanur Rahaman (Applied soft computing, 2023)
The widespread use of plastic products worldwide generates an enormous amount of waste. Plastic is a substance that is not biodegradable and is permanent in the environment. The environment and living beings are negatively affected by this waste if it is not managed properly. However, the assessment and selection of effective plastic waste management methods is a complex and uncertain decision-making problem due to the involvement of multiple conflicting attributes, the imprecise human mind, and a lack of information. Recently, interval-valued spherical fuzzy (IVSF) sets have been recognized as one of the suitable tools to handle vague information. In this paper, we introduce a hybrid multi-attribute group decision-making methodology based on the entropy method, deviation-based method, and Multi-Attribute Border Approximation area Comparison (MABAC) method with IVSF sets to choose the most effective plastic waste management process in which the decision experts’ and attribute weights are completely unknown. In this model, the entropy and deviation-based methods are utilized to calculate the decision experts’ and attribute weights, respectively. Also, the MABAC method is used to evaluate the priority order of the plastic waste management options. To do this, Dombi weighted averaging and Dombi weighted geometric operators are developed in the IVSF environment. In the proposed model, the Dombi weighted averaging operator is used to fuse several decision experts’ information, and the Dombi weighted geometric operator is used to determine the border approximation area matrix. Then, to confirm the applicability of the suggested model, we look at a numerical example of choosing the most effective method for managing plastic waste with IVSF information. In the numerical example, we consider six alternatives and four important attributes with ten sub-attributes by consulting four decision experts. The result of this study shows that ‘Recycling (A2)’ is the most effective method to reduce plastic waste. Finally, we compare the proposed method with the existing ones to demonstrate its validity. •Dombi t-conorm and t-norm operations under the IVSF environment are introduced.•Dombi weighted averaging and geometric aggregation operators of IVSFNs are developed.•A novel MABAC model is presented to solve the MAGDM problem with IVSF data.•The subjective and objective weights are combined for weighting the attributes.•The developed model is utilized to select the most effective plastic waste management method.