Author
Listed:
- Shahzaib Ashraf
- Razia Choudhary
- Muhammad Sohail
- Gokul K. C.
Abstract
Picture hesitant fuzzy soft sets (PHFSSs) are a relatively new concept in the field of soft computing, which combines hesitant fuzzy sets, fuzzy soft sets, and picture theory. This combination allows for a more comprehensive and flexible approach to decision-making problems that involve uncertainty and vagueness. They are essential when human opinion includes some sort of abstinence or rejection feature and is not just limited to yes or no. Furthermore, the idea of PHFSSs is free from all the complexity that pre-existing theories suffer from because the parametric tool with hesitancy is the key feature of PHFSS. This article demonstrates the necessity of managing the various forms of vulnerabilities and keeping an eye on procedures to address these worries. It has recently been a common issue in business management, financial modeling, estimating risks in business, and in other areas of how to choose the best investment appraisal from among those with effective values for investment. To overcome this issue, we developed the aggregation operators with multiattribute decision algorithm under picture hesitant fuzzy soft information. Furthermore, we extend our investigation to the evaluation based on the distance from average solution (EDAS) method in multiple attribute group decision making with picture hesitant fuzzy soft averaging operators. And a numerical illustration is proposed to show the accuracy of the mentioned work. Finally, we show the effectiveness and reliability of the established technique through a comparative study between these operators and the EDAS method that provides a comprehensive framework of our proposed approach.
Suggested Citation
Shahzaib Ashraf & Razia Choudhary & Muhammad Sohail & Gokul K. C., 2025.
"Optimizing Business Investments Using a Novel Approach Based on Picture Hesitant Fuzzy Soft Aggregation Information,"
Journal of Mathematics, Hindawi, vol. 2025, pages 1-22, April.
Handle:
RePEc:hin:jjmath:3886960
DOI: 10.1155/jom/3886960
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