Evaluation of Electric Motor Cars Based Frank Power Aggregation Operators Under Picture Fuzzy Information and a Multi-Attribute Group Decision-Making Process

Abstract

In this article, we expose the notion of power operator to reduce the impact of negative information on the decision-making (DM) process. The power aggregation tools are also robust mathematical aggregation operators (AOs) which allow input arguments to support each other in the DM process. The Frank aggregation expressions are reliable and updated versions of triangular norms which are used to handle complex and complicated information in a decision-making process. The picture fuzzy (PF) set (PFS) is an extended version of the fuzzy sets (FSs) and intuitionistic FSs (IFSs). A PFS has four terms of an object simultaneously such as positive grade (PG), Abstained grade (AG), negative grade (NG) and refusal grade (RG). By using basic operations of Frank aggregation expressions, we propose a list of new appropriate methodologies under consideration of PF information, including ''picture fuzzy frank power average'' (PFFPA), and ''picture fuzzy frank power geometric'' (PFFPG) operators. We also present some new approaches to PFSs based on Frank aggregation tools such as ''picture fuzzy frank power weighted average'' (PFFPWA) and ''picture fuzzy frank power weighted geometric'' (PFFPWG) operators. Some appropriate properties and special cases of our currently proposed approaches are also studied. Moreover, to ratify the intensity and reliability of our derived strategies, we illustrated an algorithm of the multiattribute group decision-making (MAGDM) technique under a PF environment. Furthermore, we illustrated a practical case study to evaluate a suitable optimal option by considering our proposed approaches and analyzed the performance of our currently derived approaches by comparing the results of existing methodologies.INDEX TERMS Frank aggregation tools, picture fuzzy numbers, power aggregation operates, multi-attribute group decision-making process.

Decision-making for solar panel selection using Sugeno-Weber triangular norm-based on q-rung orthopair fuzzy information

“…Akram and Shahzadi (2021) presented a novel approach to PyFSs by using operations of Dombi aggregation tools and developed a class of new aggregation models. Hussain et al (2023) presented Heronian mean models for selecting a suitable solar panel. By utilizing Hamacher triangular norms, Darko and Liang (2020) developed new aggregation operators (AOs) to tackle redundant information related to human opinions.…”

“…Akram et al (2023) proposed the Muirhead mean aggregation model using 2-tuple linguistic fuzzy circumstances. Hussain et al (2023) classified a suitable optimal option using the Aczel-Alsina aggregation model with an interval-valued Pythagorean fuzzy system. To reduce the impact of fuel and gas, Hussain et al (2023) evaluated an electric motor car based on the decision-making process and presented new mathematical approaches considering complex spherical fuzzy circumstances.…”

“…Hussain et al (2023) classified a suitable optimal option using the Aczel-Alsina aggregation model with an interval-valued Pythagorean fuzzy system. To reduce the impact of fuel and gas, Hussain et al (2023) evaluated an electric motor car based on the decision-making process and presented new mathematical approaches considering complex spherical fuzzy circumstances. Hussain et al (2022) also modified Hamy mean aggregation models with some specific properties to check the performance of vendor management enterprises.…”